Driving control apparatus, driving control method, and program

ABSTRACT

During autonomous driving, a reflex action is determined as a simplified action on the basis of detection results detected by a variety of sensors provided in a vehicle, and a deliberate action ranked higher than a reflex action is determined through elaborate processing. A plurality of resolution modes are made available to deal with a possible conflict between the reflex action and the deliberate action, and by which of the resolution modes the conflict is resolved is specified in advance so that the conflict is resolved by the specified resolution mode. The present disclosure is applicable to motor vehicles that drive autonomously.

TECHNICAL FIELD

The present disclosure relates to a driving control apparatus, a drivingcontrol method, and a program, and more particularly, to a drivingcontrol apparatus, a driving control method, and a program that ensureimproved safety and comfort in autonomous driving of a movable apparatussuch as motor vehicle.

BACKGROUND ART

So-called autonomous driving technology that permits driving of a motorvehicle or other vehicle using vehicle-mounted sensors, typically GPS(Global Positioning System), without driver's maneuver is on its way tomaterializing (refer, for example, PTL 1).

CITATION LIST Patent Literature [PTL 1]

JP 2008-290680A

SUMMARY Technical Problems

Incidentally, sensors are installed in motor vehicles to monitor avariety of conditions such as speed, acceleration, and position. Inautonomous driving, a next action is determined on the basis ofever-changing detection results detected by these various sensors.

However, some actions in autonomous driving such as selection of a routeand a driving lane in consideration of traffic jams require processingtime to determine using a plurality of detection results such as currentposition information, traveling speed, congestion in surrounding area,and prospect of congestion, whereas other actions in autonomous drivingsuch as avoiding collision with someone rushing out in front of themotor vehicle or with other motor vehicle have little time to spend ondecision.

Even when these processes, whose processing times required for theseactions are different, are carried out in parallel, if a conflict occursbetween requested actions, there has been a possibility that safeautonomous driving may not be realized as a result of wrong selection ofan action.

Also, even if safe autonomous driving that permits reliable travel to adestination is realized, there has been a possibility that drivingtailored to preferences of a driver (user) may not necessarily berealized, resulting in failure to realize comfortable driving.

That is, for example, when the vehicle is braked, one may feel that thevehicle is braked earlier than he or she would during driving, orconversely, later. As a result, simply riding in the vehicle may resultin stress. Thus, although the vehicle can be driven safely because ofautonomous driving, there has been a possibility that one may feelstressed while riding or comfortable driving may not be realized.

The present disclosure has been devised in light of the above problems,and it is particularly an object of the present disclosure to ensureimproved safety and comfort during travel by autonomous driving.

Solution to Problems

A driving control apparatus of an aspect of the present disclosureincludes a detection section, a deliberate action determination section,a reflex action determination section, and an action control section.The detection section detects a condition of a moving object. Thedeliberate action determination section determines an action of themoving object as a deliberate action on the basis of a detection resultof the detection section. The reflex action determination sectiondetermines, on the basis of the detection result of the detectionsection, an action of the moving object in a shorter time period than aprocess carried out by the deliberate action determination section. Theaction control section controls the action of the moving object on thebasis of the deliberate action and a reflex action determined by thereflex action determination section.

The deliberate action determination section can be caused to include alocal processing section, a global processing section, and a behaviordetermination section. The local processing section extracts localinformation around the moving object on the basis of the detectionresult of the detection section. The global processing section extractsglobal information in a wider area than around the moving object on thebasis of the detection result of the detection section. The behaviordetermination section determines an action on the basis of the localinformation and the global information.

The action control section can be caused to perform control such that ifa conflict occurs between the deliberate action and the reflex action,the occurrence of the conflict is presented.

The action control section can be caused to resolve the conflict inresponse to input from the driver and control the action of the movingobject on the basis of the deliberate action and the reflex action.

The action control section can be caused to store a plurality ofresolution modes in advance to deal with a conflict between thedeliberate action and the reflex action, resolve the conflict inaccordance with one of the plurality of resolution modes, and controlthe action of the moving object on the basis of the deliberate actionand the reflex action.

The resolution modes can be caused to include a first resolution modethat gives priority to the deliberate action or the reflex action, asecond resolution mode that selects ‘first come priority’ or ‘replacewith last come’ between the deliberate action and the reflex action, athird resolution mode that gives priority to the deliberate action orthe reflex action, whichever is higher in terms of command prioritylevel or action environment certainty level, a fourth resolution modethat takes a weighted average or majority decision using both thedeliberate action and the reflex action, a fifth resolution mode thatadds the fact that the deliberate action and the reflex action areopposed to each other to the input so that recalculation is performed bythe two, a sixth resolution mode that gives priority to the prioritylevel of the command itself for the deliberate action and the reflexaction, a seventh resolution mode that stops the vehicle without issuingeither of the deliberate action or the reflex action or maintains thecurrent state, and an eighth resolution mode that allows the driver ofthe moving object to intervene.

The action control section can be caused to display a slide bar that canbe operated to specify a parameter that is used when the deliberateaction and the reflex action are determined and control the action ofthe moving object on the basis of the deliberate action and the reflexaction determined by using the parameter whose value is proportional tothe position of the slide bar operated by the driver.

The action control section can be caused to control the action duringautonomous driving control of the moving object on the basis of thedeliberate action and the reflex action.

A driving control method of an aspect of the present disclosure includesthe steps of detecting a condition of a moving object, determining anaction of the moving object as a deliberate action on the basis of adetection result of the condition of the moving object, determining, onthe basis of the detection result, an action of the moving object in ashorter time period than a process carried out by the deliberate actiondetermination section, and controlling the action of the moving objecton the basis of the deliberate action and a reflex action determined ina shorter time period than the process for determining the deliberateaction.

A program of an aspect of the present disclosure is a program thatcauses a computer to function as a detection section, a deliberateaction determination section, a reflex action determination section, andan action control section. The detection section detects a condition ofa moving object. The deliberate action determination section determinesan action of the moving object as a deliberate action on the basis of adetection result of the detection section. The reflex actiondetermination section determines, on the basis of the detection resultof the detection section, an action of the moving object in a shortertime period than a process carried out by the deliberate actiondetermination section. The action control section controls the action ofthe moving object on the basis of the deliberate action and a reflexaction determined by the reflex action determination section.

In an aspect of the present disclosure, a condition of a moving objectis detected, an action of the moving object is determined as adeliberate action on the basis of a detection result, an action of themoving object is determined in a shorter time period than a process fordetermining the deliberate action, and the action of the moving objectis controlled on the basis of the deliberate action and a reflex actiondetermined in a shorter time period than the process for determining thedeliberate action.

Advantageous Effect of Invention

According to an aspect of the present disclosure, it is possible toensure improved safety and comfort during travel by autonomous driving.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram describing a configuration example of a drivingcontrol apparatus to which the present disclosure is applied.

FIG. 2 is a flowchart describing a driving control process by thedriving control apparatus depicted in FIG. 1.

FIG. 3 is a diagram describing a display image used for driverauthentication.

FIG. 4 is a flowchart describing an autonomous driving process depictedin FIG. 2.

FIG. 5 is a flowchart describing a deliberate action determinationprocess depicted in FIG. 4.

FIG. 6 is a flowchart describing a conflict resolution process depictedin FIG. 4.

FIG. 7 is a flowchart describing the conflict resolution processdepicted in FIG. 4.

FIG. 8 is a diagram describing what is displayed indicating theoccurrence of a conflict between a reflex action and a deliberateaction.

FIG. 9 is a flowchart describing a driver intervention resolutionprocess depicted in FIG. 6.

FIG. 10 is a diagram describing an example in which options arepresented in the driver intervention resolution process.

FIG. 11 is a diagram illustrating an example in which a slide bar ispresented in the driver intervention resolution process.

FIG. 12 is a diagram describing an example in which occurrence of aconflict is suppressed.

FIG. 13 is a flowchart describing a manual driving process depicted inFIG. 2.

FIG. 14 is a flowchart describing a personalization function updatingprocess depicted in FIG. 2.

FIG. 15 is a diagram describing a configuration example of averification apparatus to which the present disclosure is applied.

FIG. 16 is a diagram describing checkpoints.

FIG. 17 is a flowchart describing a verification process handled by theverification apparatus depicted in FIG. 15.

FIG. 18 is a diagram describing a first modification example of theverification apparatus to which the present disclosure is applied.

FIG. 19 is a diagram describing a first modification example of thedriving control apparatus to which the present disclosure is applied.

FIG. 20 is a flowchart describing the verification process handled bythe verification apparatus depicted in FIG. 18.

FIG. 21 is a flowchart describing the personalization function updatingprocess handled by the driving control apparatus depicted in FIG. 19.

FIG. 22 is a diagram describing a second modification example of theverification apparatus to which the present disclosure is applied.

FIG. 23 is a diagram describing a second modification example of thedriving control apparatus to which the present disclosure is applied.

FIG. 24 is a flowchart describing the verification process handled bythe verification apparatus depicted in FIG. 22.

FIG. 25 is a flowchart describing the personalization function updatingprocess handled by the driving control apparatus depicted in FIG. 23.

FIG. 26 is an explanatory diagram illustrating an example of positionswhere an out-vehicle information detection section and an imagingsection are installed.

FIG. 27 is a diagram describing a low power consumption action of areception action section of an existing receiver.

FIG. 28 is a diagram illustrating a configuration example of ageneral-purpose personal computer.

DESCRIPTION OF EMBODIMENTS

A detailed description will be given below of preferred embodiments ofthe present disclosure with reference to accompanying drawings. Itshould be noted that components having substantially the same functionalconfiguration are denoted by the same reference numeral in the presentspecification and the drawings to avoid duplicate descriptions.

Also, a description will be given in the following order:

1. Embodiment of the present disclosure2. First modification example3. Second modification example4. First application example5. Second application example

1. Embodiment of the Present Disclosure <Configuration Example of theDriving Control Apparatus>

FIG. 1 is a block diagram describing a configuration example of anembodiment of a motor vehicle driving control apparatus to which thepresent disclosure is applied.

The driving control apparatus depicted in FIG. 1 is mounted to a motorvehicle to control the driving thereof. It should be noted that althougha description will be given by taking, as an example, the drivingcontrol apparatus depicted in FIG. 1 that controls the driving of amotor vehicle, the driving control apparatus is applicable to othervehicles and so on so long as the vehicle can be driven (piloted) by adriver (including a pilot).

Although a driving control apparatus 11 depicted in FIG. 1 controls thedriving of a motor vehicle, there are two driving modes. A first mode ismanual driving mode in which a driver drives a motor vehicle byoperating a brake and a steering. A second mode is autonomous drivingmode in which the motor vehicle is driven automatically without driverintervention into driving operation.

This driving mode can be selectively specified by the user, and thedriving control apparatus 11 controls the motor vehicle driving in thespecified driving mode.

To be more specific, in manual driving mode, the driving controlapparatus 11 generates, by learning, a personalization function thatreflects driving habits and customs and so on of each driver based ondetection results of a detection section 34. The detection sectionincludes a variety of sensors that are linked to details of operation ofan operation section 31 by the driver such as details of operation ofthe steering and the brake (e.g., steering angle and pedal depressionforce), an outside world 12, and motor vehicle body behavior. Thedriving control apparatus 11 updates the personalization function whenthe driving ends.

In autonomous driving mode, on the other hand, the driving controlapparatus 11 controls a vehicle body action section 33 that includes aplurality of components that activate the outside world 12 and the motorvehicle body, acquires detection results of the detection section 34that includes a variety of sensors linked to the outside world 12 andthe motor vehicle body, and determines the action of each of thecomponents making up the vehicle body action section 33 to realizeautonomous driving.

Further, when the driving control apparatus 11 determines, in autonomousdriving mode, an action of each of the components making up the vehiclebody action section 33 based on a detection result of the detectionsection 34 that includes various sensors, the driving control apparatus11 corrects an operative action using the personalization functionobtained by learning, and realizes autonomous driving tailored todriver's habits and customs by activating each of various componentsmaking up the vehicle body action section 33.

To be more specific, in autonomous driving mode, the driving controlapparatus 11 finds two kinds of actions, a deliberate action and areflex action, based on the detection result of the detection section34, and determines a final autonomous driving action based on the foundtwo kinds of actions.

Here, a deliberate action refers to an action that is determined withsufficiently high accuracy through elaborate processing by using thedetection result of the detection section 34 although it requires arelatively long processing time. A deliberate action is used when anaction requiring an extremely small amount of time is not needed.

On the other hand, a reflex action of the detection section 34 refers toan action that is determined speedily without spending much time throughsimpler processing than that for determining a deliberate action. Areflex action is used primarily when an action is needed in a short timeperiod.

The driving control apparatus 11 determines details of the action ofeach of the various components making up the vehicle body action section33 to realize autonomous driving by using these deliberate and reflexactions.

To be more specific, the driving control apparatus 11 includes anautonomous driving control block 21, a personalization block 22, anoperation section 31, a manual driving control section 32, a vehiclebody action section 33, a detection section 34, and a display section35.

The autonomous driving control block 21 controls the action of each ofcomponents making up the vehicle body action section 33 in autonomousdriving mode based on various detection results detected by thedetection section 34 and a personalization function.

In contrast, the manual driving control section 32 controls the actionof each of components making up the vehicle body action section 33 inmanual driving mode in response to an operation signal at the time ofoperation of each of components such as steering or brake by the driverto activate the vehicle body.

The personalization block 22 finds, based on details of operation of theoperation section 31 operated by the driver in manual driving mode anddetection results of the detection section 34 in response to action ofeach of the various components making up the vehicle body action section33, a personalization function of the driver and supplies the functionin autonomous driving mode. A personalization function is designed toreflect personal habits and customs in driving action. Therefore, as theaction of each of the various components making up the vehicle bodyaction section 33 determined in autonomous driving mode is correctedbecause of the use of a personalization function, it is possible tocustomize the driving action in autonomous driving mode by reflectinghabits and customs of each driver, thereby ensuring improved comfort inautonomous driving.

In addition to various operational apparatuses related to driving suchas steering, brake pedal, and accelerator pedal, the operation section31 generates operation signals for almost all operations of those thatcan be operated in the motor vehicle by the driver, a user, ranging fromoperational apparatuses such as turn signals, windshield wipers, windowwashers, horn, lights, and instrument panel related to operation ofvarious components making up the motor vehicle body to which the drivingcontrol apparatus 11 is mounted to operational apparatuses for switchingbetween manual driving mode and autonomous driving mode. The operationsection 31 supplies operation signals to the personalization block 22and the manual driving control section 32.

The manual driving control section 32 supplies, based on the operationsignals supplied from the operation section 31, commands instructingvarious actions to the vehicle body action section 33 and activatesvarious components for activating the motor vehicle body making up thevehicle body action section 33.

The vehicle body action section 33 includes a specific group ofcomponents for activating the motor vehicle body and is, for example, agroup of various components for activating the motor vehicle body suchas steering wheel, brake, and engine.

The detection section 34 includes, a group of sensors for detectingvarious states related to the action of the motor vehicle body to whichthe driving control apparatus 11 is mounted. These sensors include GPS(Global Positioning System) for detecting the motor vehicle's position,steering wheel steering angle, speed, and 3D acceleration sensors, yaw,roll, and pitch sensors, cameras (image sensors) (including stereocamera sensors), rain drop detection sensor, dense fog sensor,illuminance sensor, atmospheric pressure sensor, tire pressure sensor,millimeter wave radar (millimeter wave sensor), infrared sensor, beaconsensor, and temperature, pressure, and other sensors of variouscomponents. The detection section 34 supplies detection results to theautonomous driving control block 21 and the personalization block 22.

The display section 35 is a display apparatus that includes, forexample, an LCD (Liquid Crystal Panel) provided in the instrument paneland displays the current driving mode, either autonomous driving mode ormanual driving mode, or various kinds of information in autonomousdriving mode or manual driving mode. The display section 35 may have anintegral structure with the operation section 31 to function, forexample, as a touch panel. By having such a configuration, operatingbuttons for switching between autonomous driving mode and manual drivingmode, for example, may be displayed so that these modes are switched byaccepting input through touch operation.

The autonomous driving control block 21 is a block that determines theaction of each component of the vehicle body action section 33 of themotor vehicle in autonomous driving mode. To be more specific, theautonomous driving control block 21 includes a reflex actiondetermination section 51, a deliberate action determination section 52,an autonomous driving control section 53, and a personalization functionstorage section 54.

The reflex action determination section 51 determines, based ondetection results of the detection section 34, an action of each of thevarious components making up the vehicle body action section 33 inautonomous driving mode by a process simpler than that carried out bythe deliberate action determination section 52 which will be describedlater and supplies the command that matches the determined action to theautonomous driving control section 53.

The reflex action determination section 51 decides that there is a riskof collision, for example, when the distance to the motor vehicle infront is shorter than a given distance and when the speed is higher thana given speed, and determines, for example, an action of activating aso-called pre-clash safety apparatus for taking emergency avoidancebehavior such as steering action or automatic brake. Then, the reflexaction determination section 51 reads, from the personalization functionstorage section 54, a personalization function that has the habits andcustoms of each driver reflected and specified therein, corrects thecommand associated with the reflex action in such a manner as to reflectdriver's preferences, and supplies the command to the autonomous drivingcontrol section 53.

That is, a reflex action includes a number of highly urgent actions thatrequire a decision in an extremely short period of time. Therefore, areflex action may include, to a certain extent, a number ofpredetermined actions with respect to detection results, and this makesit possible to determine an action that allows for response in anextremely short time period. Hereinafter, an action determined by thisreflex action determination section 51 will be simply referred to as areflex action.

The deliberate action determination section 52 determines, based ondetection results of the detection section 34, an action of each of thevarious components making up the vehicle body action section 33 inautonomous driving mode by a process more elaborate than that carriedout by the reflex action determination section 51, and supplies theassociated command to the autonomous driving control section 53. Then,the deliberate action determination section 52 reads, from thepersonalization function storage section 54, a personalization functionthat has the habits and customs of each driver reflected and specifiedtherein, corrects the command associated with the deliberate action insuch a manner as to reflect driver's preferences, and supplies thecommand to the autonomous driving control section 53.

Thus, as the driver's preferences are reflected into the reflex actionand deliberate action, it is possible to ensure improved comfort foreach driver in autonomous driving mode.

The deliberate action determination section 52 determines an action ofcontrolling steering operation, for example, when one passes an oncomingvehicle on a narrow road, estimating the ever-changingvehicle-to-vehicle distance between one's own vehicle and the oncomingvehicle and the motion of the vehicle body to suit the steeringoperation conducted a plurality of times and determining a relativelytime-consuming action such as an action that suits the estimationresults. Hereinafter, an action determined by the deliberate actiondetermination section 52 will be simply referred to as a deliberateaction.

The autonomous driving control section 53 determines an action of thevehicle body action section 33 in autonomous driving mode based on areflex action command supplied from the reflex action determinationsection 51 and a deliberate action command supplied from the deliberateaction determination section 52 and supplies the associated command tothe vehicle body action section 33.

The reflex action determination section 51 can, in general, determine areflex action quicker than the processing time required until adeliberate action is determined by the deliberate action determinationsection 52. It should be noted, however, that, depending on theconditions of the detection results obtained from the detection section34, the processing time required until a deliberate action is determinedmay be shorter than the processing time required until a reflex actionis determined, and that the processing times may be approximately thesame.

Further, the autonomous driving control section 53 determines an actionbased on a reflex action and a deliberate action, and in general, on thepremise that mutual processing results agree with each other, andsupplies the associated action signal to the vehicle body action section33.

However, a reflex action and a deliberate action may conflict with eachother depending on the detection results. Therefore, an autonomousdriving action is determined by a resolution mode selected from amongthe following plurality of resolution modes:

That is, there are seven (7) resolution modes, i.e., a first resolutionmode that gives priority to a deliberate action or a reflex action, asecond resolution mode that selects ‘first come priority’ or ‘replacewith last come,’ a third resolution mode that gives priority towhichever is higher in terms of priority level or certainty level, afourth resolution mode that takes a weighted average using both actionsor majority decision, a fifth resolution mode that adds the fact thatthe two are opposed to each other to the input so that recalculation isperformed by the two, a sixth resolution mode that gives priority topriority levels of commands themselves, and a seventh resolution modethat stops the vehicle without issuing either or maintains the currentstate. Further, there is an eighth resolution mode that allows thedriver's decision to intervene, which makes a total of eight kinds ofresolution modes. It should be noted that the eight kinds of resolutionmodes cited here are merely examples, and that other resolution modesmay be further specified.

It is possible to specify, by using the operation section 31 in advance,which of the eight kinds of resolution modes described above is used toresolve a conflict. Therefore, the autonomous driving control section 53stores details of resolution mode setting, determines an action of thevehicle body action section 33 in autonomous driving mode in accordancewith the stored resolution mode using deliberate and reflex actions, andsupplies the action to the vehicle body action section 33.

The deliberate action determination section 52 includes an environmentrecognition section 71, a local map processing section 72, a global mapprocessing section 73, a route planning section 74, and a behaviorplanning section 75.

The environment recognition section 71 recognizes the environmentsurrounding the own vehicle, generates environmental information as arecognition result, and supplies the information to the local mapprocessing section 72. Environmental information of the own vehicle isinformation required for the local map processing section 72 and theglobal map processing section 73 and includes, for example, GPSinformation indicating a position on earth (position on a routespecified as a route on a map) and images captured by image sensors orother devices to recognize the lane on the road being travelled and theroad conditions. Environmental information also includes surroundingenvironmental information, traffic jam information, and so on such asbeacon information including traveling speed of the own vehicle,weather, and traffic information.

The local map processing section 72 extracts, as local information,local map-based narrow-range information around the vehicle such asposition of the lane on the road being travelled, traveling speed,detailed shape of the road, traffic signs, traffic lights, and so onfrom the environmental information extracted based on the detectionresults and supplies the information to the behavior planning section75. The local map processing section 72 also supplies the environmentalinformation to the global map processing section 73.

The global map processing section 73 extracts, as global information,global map-based wide-range information around the vehicle such asbeacon information and GPS information that is included in theenvironmental information ranging from traffic jam condition andaccident information to prospect of traffic jams in the route from theorigin to destination and supplies the information to the route planningsection 74.

That is, local information is information in a relatively narrow rangein connection with the surroundings of the motor vehicle body based on alocal map (map information that covers a relatively short distance fromthe vehicle body). In contrast, global information is information in arelatively wide range in connection with the surroundings of the motorvehicle body on the route to be travelled from now based on a global map(map information that covers a relatively long distance from the vehiclebody).

The route planning section 74 plans a traveling route of the own vehiclebased on global information supplied from the global map processingsection 73 and supplies the route to the behavior planning section 75 asroute planning information.

The behavior planning section 75 plans a behavior for activating thevehicle body action section 33 based on the local information and theroute planning information and supplies the associated command as adeliberate action. More specifically, the behavior planning section 75determines, for example, a steering angle of the steering, brakingtiming, accelerator opening angle, and so on required to change the laneas a deliberate action when it is necessary to change the lane becauseof the relationship between the route such as turning right or left nextand the currently travelled lane based on detailed road shape andtravelled lane information, local information, and route informationfound from the global information. The behavior planning section 75supplies the command associated with the deliberate action to theautonomous driving control section 53.

The personalization block 22 includes a personalization functionlearning section 91, a learning result storage section 82, a learningresult verification section 93, a verification result decision section94, and a personalization function updating section 95.

The personalization function learning section 91 finds, by learning, apersonalization function for each driver based on an operation signalsupplied from the operation section 31 and various detection resultssupplied from the detection section 34 and stores the function in thelearning result storage section 92. That is, the personalizationfunction learning section 91 is designed to find, by learning, apersonalization function that reflects driving habits and customs of thedriver based on an operation signal during driving by the driver byactually operating the operation section 31 in manual driving mode andbased on the detection results of the detection section 34 at that time.Therefore, in accordance with the length of driving time in manualdriving mode, the longer the learning time, the more strongly apersonalization function reflects the habits and customs of each driver.

Also, the personalization function learning section 91 may specify aplurality of personalization functions for the same driver. That is, thedriving action of the driver is not always constant but changesdepending on the physical and mental conditions.

Therefore, it is possible to specify a requested personalizationfunction as a personalization function for each mood of the driver foreach of the plurality of driving modes.

For example, a personalization function used when one drives in a “slowand safe” manner requested from an operation signal with slow brakingand accelerating operations can be used as a first mode. Also, apersonalization function used when one drives in a “speedy” mannerrequested from an operation signal for braking operation that stops thevehicle over a short distance or an operation signal for repeatedlydepressing and releasing the accelerator pedal in an intensive mannercan be used as a second mode. Then, a third personalization functionobtained from the average or weighted average of the parameters forthese “slow and safe” and “speedy” manners can be used as a third mode.

Thus, by specifying a plurality of personalization functions for thesame driver to match the mood of the driver in manual driving mode, itis possible to change the autonomous driving action to suit the mood ofthe driver at that time, thereby contributing to improved comfort inautonomous driving. It should be noted that this mode tailored to themood of each driver in a personalization function will be referred to asa user mode. Therefore, it is possible for the driving control apparatus11 to learn a personalization function in manual driving mode for eachdriver and for each user mode, and it is possible to make adequatecorrection in autonomous driving mode for each driver and for each usermode.

The learning result verification section 93 reads the personalizationfunction, a learning result stored in the learning result storagesection 92, when the driving is over, supplies the personalizationfunction to an external verification apparatus 13 via a network,typically, the Internet, requests verification of the personalizationfunction, and acquires a verification result.

The verification apparatus 13 is an apparatus realized, for example, bycloud computing. When a request is made by the driving control apparatus11 to verify a personalization function, the verification apparatus 13verifies safety by virtually using the personalization function andrealizing autonomous driving through simulation and supplies theverification result. To be more specific, the verification apparatus 13corrects the command virtually determined by the autonomous drivingcontrol section 53 using the personalization function and repeatedlysimulates the activation of the vehicle body action section 33 for a settime period, thereby reproducing autonomous driving using thepersonalization function, recording traveling information at this timeas a verification result, and supplying the verification result to thedriving control apparatus 11. It should be noted that a detailedconfiguration of the verification apparatus 13 will be described laterwith reference to FIG. 15.

When the verification result, a simulation result using thepersonalization function, is acquired, the verification result decisionsection 94 verifies whether or not the personalization function isguaranteed safe based, for example, on whether or not an anticipatedrisk-avoiding behavior was fully taken with no accidents during thesimulation. Then, the verification result decision section 94 decidesthe verification result of the verification apparatus 13 and suppliesthe decision result to the personalization function updating section 95.

When the decision result can be considered safe with no possibility ofaccidents even after correction of the command with a personalizationfunction, the personalization function updating section 95 reads thepersonalization function stored in the learning result storage section92 and whose safety is guaranteed by the verification apparatus 13, andupdates the personalization function stored in the personalizationfunction storage section 54.

Through such a series of processes, it is possible to correct a varietyof commands for the vehicle body action section 33 using apersonalization function having the user's preferences reflected thereinand whose safety is guaranteed and realize driving control processes inautonomous driving mode. Consequently, it is possible to realize safeand comfortable autonomous driving in autonomous driving mode. It shouldbe noted that if there is a problem with the verification result of thepersonalization function supplied to the verification apparatus 13, datain the case of occurrence of the problem may be further supplied fromthe verification apparatus 13 so that the data is fed back to thepersonalization function learning section 91 for relearning.

<Driving Control Process>

A description will be given next of a driving control process handled bythe driving control apparatus 11 depicted in FIG. 1 with reference tothe flowchart depicted in FIG. 2. It should be noted that althougheither autonomous driving mode or manual driving mode is normallyspecified as a driving mode, we assume here that manual driving mode isspecified as a default mode and that the driving mode can be switched toautonomous driving mode after the driving begins. Also, the defaultdriving mode may be either one of autonomous driving mode and manualdriving mode, and either mode may be freely specified.

In step S11, the manual driving control section 32 decides whether ornot the driving has been started by operating the operation section 31and repeats the same process until the driving is started. That is, inthis case, for example, a decision as to whether or not the driving hasbeen started may be made based on whether or not the operation section31 that includes a start button and so on for starting the engine andenabling driving operation has been operated. In step S11, when it isdecided that the driving has been started, the process proceeds to stepS12.

In step S12, the manual driving control section 32 authenticates thedriver. For example, the manual driving control section 32 displays, onthe display section 35, a display image that looks as if it promptsinformation input for identification of the driver depicted on the leftin FIG. 3, accepts operation input, and identifies the driver inaccordance with details of operation accepted.

It should be noted that an example of a display image displayed assumingthat the display section 35 is a touch panel integral with the operationsection 31 is depicted on the left in FIG. 3. “Driver Check” is depictedat the topmost row, and operation buttons 101-1 to 101-3 are depictedthereunder from left. At the corresponding positions, “Taro,” “Hanako,”and “Jiro” appear as drivers' names registered in advance. Then, acolumn 102 is displayed on the left in FIG. 3 that depicts that “Jiro”is selected as a result of operation of the operation button 101-3. Inthis case, therefore, the manual driving control section 32 recognizesthat the driver is “Jiro.” Also, if the driver is a new user, aregistration image may be displayed separately to prompt registration.

Also, the identification of the driver may be realized by face imagerecognition using a camera that captures an image inside the vehicle.Alternatively, other authentication method such as fingerprintauthentication, palm authentication, vein authentication, retinaauthentication, and voice print authentication may be used as long asthe driver can be identified.

In step S13, the manual driving control section 32 specifies a usermode. That is, for example, the manual driving control section 32displays an image that depicts user modes, modes of the personalizationfunction specified to suit the mood of the driver as depicted on theright of FIG. 3, prompts selection of one of the user modes, acceptsoperation input, and identifies the user mode in accordance with detailsof operation accepted.

That is, on the right in FIG. 3, “Jiro's Driving Today” is depicted atthe topmost row, and selectable user modes are depicted thereunder, withbuttons 105-1 to 105-3 appearing from left. At the correspondingpositions, “Slow and Safe,” “Balanced,” and “Speedy” appear as usermodes. Then, a column 106 is displayed on the right in FIG. 3 thatdepicts that “Speedy” is selected as a result of operation of the button105-3. In such a case, the manual driving control section 32 recognizesthat the user mode is “Speedy.”

It should be noted that a user mode may be specified by using meansother than the touch panel. For example, a user mode may be specified byaudio input. Alternatively, a user mode may be selected by a physicalbutton or switch. In the meantime, a new user mode may be specified, andin this case, an image may be displayed to prompt registration of a newuser mode.

In step S14, the manual driving control section 32 displays an image toprompt specification of a resolution mode for resolving a conflict whichmay occur between a deliberate action and a reflex action in autonomousdriving mode and stores the specified resolution mode in the autonomousdriving control section 53.

That is, one of eight (8) kinds of resolution modes is specified, i.e.,a first resolution mode that gives priority to a deliberate action or areflex action, a second resolution mode that selects ‘first comepriority’ or ‘replace with last come,’ a third resolution mode thatgives priority to whichever is higher in terms of priority level orcertainty level, a fourth resolution mode that takes a weighted averageusing both actions or majority decision, a fifth resolution mode thatadds the fact that the two are opposed to each other to the input sothat recalculation is performed by the two, a sixth resolution mode thatgives priority to priority levels of commands themselves, a seventhresolution mode that stops the vehicle without issuing either ormaintains the current state, or an eighth resolution mode that acceptsthe driver's intervention for resolution. Also, if there are options inany of the resolution modes, the selection of an option is specified.

Specifically, this process may be conducted, for example, by displayingan image in which selection buttons are provided not only to select oneof the first to eighth resolution modes but also, in the presence offurther options in each resolution mode, to select one of the options,as done on the right in FIG. 3 so that the resolution mode whoseselection button has been pressed is specified. Selection buttons thatallow physical selection of a resolution mode at all times may beprovided on the operation section 31. Alternatively, one of theresolution modes is selected in a fixed manner at all times.

A resolution mode with options refers, for example, to the firstresolution mode. That is, because the first resolution mode is a modethat gives priority to a deliberate action or a reflex action, an itemto which priority should be given, i.e., deliberate action or reflexaction, serves as an option. For this reason, when the first resolutionmode is selected, it is also necessary to specify an option, deliberateaction or reflex action. In the resolution modes other than the fifth,sixth, and eighth resolution modes, it is similarly necessary to specifyan option.

It should be noted that the resolution mode selection process in thisstep S14 is not always necessary once it is specified. Therefore, thisprocess may be performed only when requested by the driver.Alternatively, one of the modes may be specified as a default mode.Further, if a physical button is provided, the setting may be changedimmediately when the physical button is operated irrespective of whenthe button is operated.

In step S15, the manual driving control section 32 decides whether ornot the driving mode is autonomous driving mode. As for a decision as tothe driving mode which is either autonomous driving mode or manualdriving mode, for example, whether or not the driving mode has beenchanged may be decided by decision whether or not the switchingoperation was performed, for example, by operating a selector switch(not depicted) that appears constantly on the display section 35.

Also, a physical switch or button (both not depicted) may be provided sothat the driving mode can be changed. When it is assumed that theswitching operation was performed and that manual driving mode, adefault mode, has been switched over to autonomous driving mode in stepS15, the process proceeds to step S16 to perform an autonomous drivingprocess. In this case, the section that mainly takes charge of controlis switched from the manual driving control section 32 over to theautonomous driving control section 53 so that the autonomous drivingcontrol section 53 handles the autonomous driving process.

On the other hand, when the driving mode remains the default mode,namely, manual driving mode, rather than autonomous driving mode, instep S15, the process proceeds to step S17 to perform a manual drivingprocess. In this case, the manual driving control section 32 remains thesection that mainly takes charge of control and handles the manualdriving process.

Also, when the autonomous driving process has been performed so far, andwhen the driving mode is switched to manual driving mode as a result ofthe process in step S15, the manual driving process is performed in stepS17. In this case, the section that mainly takes charge of control isswitched from the autonomous driving control section 53 over to themanual driving control section 32 so that the manual driving controlsection 32 handles the manual driving process.

It should be noted that a description will be hereinafter given byassuming that manual driving mode, the default mode, is selected, thatis, the manual driving control section 32 mainly takes charge ofcontrol, unless otherwise specified. It should be noted, however, thatwhen a process is performed in autonomous driving mode, the autonomousdriving control section 53 takes charge of control. As for the processesdescribed in the flowchart depicted in FIG. 2, the same processes as forthe manual driving control section 32 are performed. Also, theautonomous driving and manual driving processes will be described indetail later.

In step S18, the manual driving control section 32 decides whether ornot the operation for terminating the driving was performed by operatingthe operation section 31. When the operation for terminating the drivinghas yet to be performed in step S18, the process proceeds to step S19.

In step S19, the manual driving control section 32 decides whether ornot the drivers have been changed. For example, the manual drivingcontrol section 32 decides whether or not any operation was performed torequest a change to the driver as a result of operation of the operationsection 31. If, for example, the driver has been changed in step S19,the process returns to step S12. That is, the driver authenticationprocess, the user mode specification, and the resolution modespecification are performed on the changed driver by the processes fromstep S12 to step S14, followed by the subsequent processes.

On the other hand, when the driver is not changed in step S19, theprocess returns to step S15. That is, the processes from step S12 tostep S14 are skipped.

When it is assumed in step S18 that the operation for terminating thedriving was performed, the process proceeds to step S20.

In step S20, the personalization block 22 performs a personalizationfunction updating process, verifying the personalization functionlearned by manual driving and updating the personalization function inaccordance with the verification result. It should be noted that thepersonalization function updating process will be described in detaillater.

Because of the processes described heretofore, it is possible to realizedriving control that switches between autonomous driving mode and manualdriving mode and make it also possible to generate, by learning, apersonalization function learned in manual driving mode which will bedescribed later and further update the personalization function.

<Autonomous Driving Process>

A description will be given next of the autonomous driving processhandled by the driving control apparatus 11 depicted in FIG. 1 withreference to the flowchart depicted in FIG. 4.

In step S31, the detection section 34 supplies all of a plurality ofdetection results detected by a group of various sensors to theautonomous driving control block 21 and the personalization block 22.

In step S32, the reflex action determination section 51 determines areflex action on the basis of the detection results (or some of thedetection results).

In step S33, the reflex action determination section 51 reads, of thepersonalization functions stored in the personalization function storagesection 54, the function of the authenticated driver that is associatedwith the currently specified user mode and corrects the actiondetermined as a reflex action with the personalization function.

In step S34, the deliberate action determination section 52 determines adeliberate action by performing a deliberate action determinationprocess.

<Deliberate Action Determination Process>

A description will be given here of the deliberate action determinationprocess with reference to the flowchart depicted in FIG. 5.

In step S51, the environment recognition section 71 extracts environmentinformation on the basis of the detection results supplied from thedetection section 34 and supplies the information to the local mapprocessing section 72.

In step S52, the local map processing section 72 extracts, from theenvironment information, local information around the own vehicle, andsupplies the information to the behavior planning section 75. Also, thelocal map processing section 72 supplies the environment information tothe global map processing section 73.

In step S53, the global map processing section 73 extracts, from theenvironment information, global information that includes mapinformation of the areas surrounding the route that will be travelled bythe own vehicle from now and traffic information on the route andsupplies the global information to the route planning section 74.

In step S54, the route planning section 74 plans a traveling route ofthe own vehicle based on the global information supplied from the globalmap processing section 73 and supplies the route to the behaviorplanning section 75 as a route plan. That is, the route planning section74 searches for routes from the current position to the destinationbased, for example, on traffic information and plans, in the presence oftraffic jam on the route, a route by searching for a route that leads tothe destination while avoiding the traffic jam.

In step S55, the behavior planning section 75 plans a behavior foractivating the vehicle body action section 33 based on the localinformation and the route plan, considers the planning result as adeliberate action, and supplies the command associated with thedeliberate action to the autonomous driving control section 53. That is,the behavior planning section 75 determines, for example, a steeringangle of the steering, braking timing, accelerator opening angle, and soon required to change the lane as a deliberate action when it isnecessary to change the lane because of the relationship between theroute such as turning right or left next and the currently travelledlane based on detailed road shape and travelled lane information, localinformation, and route information found from the global information.The behavior planning section 75 supplies the command associated withthe deliberate action to the autonomous driving control section 53.

Because of the above processes, environment information is found fromthe detection results, local and global information is found from theenvironment information, a route is specified from the globalinformation, and a deliberate action is found from the specified routeand the local information.

Here, we return to the description of the flowchart depicted in FIG. 4.

In step S35, the behavior planning section 75 of the deliberate actiondetermination section 52 reads, of the personalization functions storedin the personalization function storage section 54, the function of theauthenticated driver that is associated with the currently specifieduser mode and corrects the action determined as a deliberate action withthe personalization function.

In step S36, the autonomous driving control section 53 decides whetheror not there is a conflict between the deliberate action and the reflexaction because of a mismatch therebetween. When it is determined in stepS34 that there is a conflict, the process proceeds to step S35.

In step S37, the autonomous driving control section 53 resolves theconflict between the deliberate action and the reflex action byperforming a conflict resolution process, determines an action to beperformed by the vehicle body action section 33, and supplies thecommand associated with the determined action to the vehicle body actionsection 33. It should be noted that the conflict resolution process willbe described in detail later with reference to FIGS. 6 and 7.

It should be noted that when it is decided in step S36 that there is noconflict, the process in step S37 is skipped.

Then, in step S38, the autonomous driving control section 53 supplies,to the vehicle body action section 33, the command associated with theaction to be performed by the vehicle body action section 33. That is,when there is a match between the reflex action and the deliberateaction, the autonomous driving control section 53 supplies the commandassociated with the matching action to the vehicle body action section33. When there is a conflict between the reflex action and thedeliberate action because of a mismatch therebetween, the autonomousdriving control section 53 supplies, to the vehicle body action section33, the command associated with the action determined by the conflictresolution process. As a result, the vehicle body action section 33 actsin accordance with the command from the autonomous driving controlsection 53.

As a result, as will be described later, as a reflex action and adeliberate action is individually corrected by a personalizationfunction that is learned when the driver himself or herself drives inmanual driving mode, it is possible to reflect the habits and customs ofthe authenticated driver into the actions, making it possible to realizesafe autonomous driving and comfortable autonomous driving tailored toeach driver.

It should be noted that FIG. 4 states that a series of reflexaction-related processes including the determination of a reflex actionand the correction of the personalization function for the reflex actiondetermined, realized by the processes in steps S32 and S33, areperformed first, followed by a series of deliberate action-relatedprocesses including the determination of a deliberate action and thecorrection of the personalization function for the deliberate actiondetermined realized by the processes in steps S34 and S35.

However, the reflex action-related processes and the deliberateaction-related processes described above are processes performedindividually by the reflex action determination section 51 and thedeliberate action determination section 52 that are configured inparallel between the detection section 34 and the autonomous drivingcontrol section 53, as is also evident from the block diagram depictedin FIG. 1. Therefore, the reflex action-related processes and thedeliberate action-related processes are processes performed in parallel,i.e., simultaneously. Although the flowchart depicted in FIG. 4 depictsthese processes as if the reflex action-related processes are performedfirst, followed by the deliberate action-related processes, this is aresult of depiction for convenience with a single flowchart. As a matterof course, it may be depicted that the deliberate action-relatedprocesses are performed first, followed by the reflex action-relatedprocesses. Also, for the same reason, the reflex action-relatedprocesses and the deliberate action-related processes may be depicted asindividual flowcharts that are processed simultaneously in parallel. Inthis case, the processes from step S36 onward in FIG. 4 are performedonly after both the reflex action-related processes and the deliberateaction-related processes are complete.

<Conflict Resolution Process>

A description will be given next of the conflict resolution process withreference to the flowcharts depicted in FIGS. 6 and 7.

In step S71 (FIG. 6), the autonomous driving control section 53 presentsthe occurrence of a conflict between the deliberate action and thereflex action to the driver by displaying information indicating theoccurrence of a conflict to the display section 35 because of a mismatchbetween the deliberate action and the reflex action. The autonomousdriving control section 53 displays a mark 124 indicating the occurrenceof a conflict in an instrument panel 111 of the motor vehicle to whichthe driving control apparatus 11 is mounted, corresponding to thedisplay section 35, for example, as depicted in FIG. 8. It should benoted that a speedometer 121, a tachometer 122, and a fuel gauge 123appear from left each in the form of a disk-shaped meter with a needlein the instrument panel 111 depicted in FIG. 8, and that the mark 124indicating the occurrence of a conflict appears at the top left of thefuel gauge 123 as a mark that includes arrows pointing in threedirections. The driver can recognize a conflict between the deliberateaction and the reflex action because of a mismatch therebetween byvisually recognizing this mark 124. The driver can perceive apossibility that he or she may switch to manual driving mode by himselfor herself and drive manually as necessary, making it possible to keepto a minimum inadvertent action as a result of a sudden need to drivehimself or herself.

It should be noted that although an example is depicted in which themark 124 is displayed and presented to the driver as an example ofoccurrence of a conflict, the occurrence of a conflict may be presentedin other manner. For example, the occurrence of a conflict may bepresented by audio, sheet vibration, and so on.

In step S72, the autonomous driving control section 53 decides whetheror not the resolution mode in the event of occurrence of a conflict is aresolution mode that preferentially selects the deliberate action or thereflex action over the other. For example, when it is decided in stepS72 that the resolution mode is not a mode that preferentially selectsthe deliberate action or the reflex action over the other, the processproceeds to step S73.

In step S73, the autonomous driving control section 53 selects, of theresolution modes specified in advance, the specified action, either thedeliberate action or the reflex action, as a determined action, and theprocess proceeds to step S85 (FIG. 7).

We assume, for example, that the reflex action is an action likefollowing the vehicle in front while remaining on the currently traveledlane, and that the deliberate action is an action that suits the resultof search for a route that avoids construction work and traffic jam inconsideration of the route to the destination.

Here, when the setup is such that priority is given to the deliberateaction, and when the optimal route is changed, for example, because ofnew traffic information acquired, priority will be given to an actionsuch as traveling the route found by a search for a route that avoidsconstruction work and traffic jap as a deliberate action. As a result,an action is implemented that guides the motor vehicle to a detour foravoiding the traffic jam as a motor vehicle's route, thereby ensuringreduced time required.

We also assume that the reflex action is an action that performs anemergency brake operation if an obstacle of a given size or larger isdetected by forward millimeter wave radar, and that the deliberateaction is an action that realizes in-lane driving at constant speedtailored to the surrounding environment.

Here, when the setup is such that priority is given to the reflexaction, and if someone rushes out onto the road, it is possible to avoidan accident by an extremely brief action based on the reflex action.

Also, in step S72, when it is determined that the resolution mode is notthe one that preferentially selects the deliberate action or the reflexaction over the other, the process proceeds to step S74.

In step S74, the autonomous driving control section 53 decides whetheror not the resolution mode in the event of occurrence of a conflict is aresolution mode that selects ‘first come priority’ or ‘replace with lastcome.’ When it is decided in step S74 that the resolution mode is not amode that selects ‘first come priority’ or ‘replace with last come,’ theprocess proceeds to step S75.

In step S75, the autonomous driving control section 53 selects, of theresolution modes specified in advance, the action specified for thespecified scheme, either ‘first come priority’ or ‘replace with lastcome,’ as a determined action, and the process proceeds to step S85(FIG. 7).

The commands that indicate the deliberate action and the reflex actioneach specify the execution times expressly or implicitly (e.g., 4 ms).Normally, commands are accumulated in a list in the order of arrival andare executed starting from the first one in the list. As a result, theaction is determined on a ‘first come priority’ basis. This realizesaccelerator and steering control, predictive driving, and so on in aconstant time loop. Therefore, when ‘first come priority’ is specified,the action is determined by common processes.

Also, each control module issues a command in a timely manner inresponse to a change in circumstances such as interrupt and does notperform anything unless the behavior up to that moment is changed. Onthe other hand, if the command representing the action up to that momentis overwritten by a new command that arrives later when such a commandarrives, and if the action is immediately switched over to the onerepresented by the later command, a speedy action can be realized. Inthis case, therefore, whether the resolution mode selects the deliberateaction or the reflex action is not a factor that determines the action,and the current action command is overwritten by the action command thatarrives later in any case.

Also, when it is decided in step S74 that the resolution mode is not amode that selects ‘first come priority’ or ‘replace with last come,’ theprocess proceeds to step S76.

In step S76, the autonomous driving control section 53 decides whetheror not the resolution mode in the event of occurrence of a conflict is aresolution mode that selects whichever is higher in terms of prioritylevel or certainty level. When it is decided in step S76, for example,that the resolution mode is a mode that selects whichever is higher interms of priority level or certainty level, the process proceeds to stepS77.

In step S77, the autonomous driving control section 53 selects, of theresolution modes specified in advance, the action with higher prioritylevel or certainty level, as a determined action, and the processproceeds to step S85 (FIG. 7).

Commands that indicate various deliberate and reflex actions that areurgently issued in response to a change in circumstances such asinterrupts have a high priority flag. If the priority level flag for thecommand accumulated in the list or the command being executed is lowerthan that of a new command, the autonomous driving control section 53replaces the command in the list or the command being executed with thenew one (e.g., emergency braking) even through cancellation. In thiscase, therefore, the determined action may be a reflex action or adeliberate action.

Also, the reflex action and the deliberate action may be equal in termsof priority level, and either thereof may be selected in accordance withthe reliability level of information recognized as environmentinformation.

That is, we assume, for example, that the reflex action and thedeliberate action are speed increasing action and speed reducing action,individually. In such a case, for example, when environment informationto the effect that there is no vehicle ahead is highly reliable,increasing the speed will be a determined action. When environmentinformation to the effect that there is an obstacle ahead is highlyreliable, reducing the speed will be a determined action.

Also, we assume, for example, that the reflex action and the deliberateaction are an action of passing the vehicle in front traveling in thesame direction as the own vehicle and an action of following the vehiclein front traveling in the same direction as the own vehicle,individually. In this case, when environment information to the effectthat the vehicle in front traveling in the same direction as the ownvehicle is a bicycle is highly reliable, passing the bicycle may be adetermined action, and when environment information to the effect thatthe vehicle in front traveling in the same direction as the own vehicleis a motor vehicle is highly reliable, following the motor vehicle maybe a determined action.

Also in this case, therefore, the determined action may be a reflexaction or a deliberate action.

When it is decided in step S76 that the resolution mode is not a modethat selects whichever is higher in terms of priority level or certaintylevel, the process proceeds to step S78.

In step S78, the autonomous driving control section 53 decides whetheror not the resolution mode in the event of occurrence of a conflict is aresolution mode that determines an action by weighted average ormajority decision. When it is decided in step S78, for example, that theresolution mode is a mode that determines an action by weighted averageor majority decision, the process proceeds to step S79.

In step S79, the autonomous driving control section 53 selects, of theresolution modes specified in advance, the specified action, the actiondetermined by weighted average or majority decision, as a determinedaction, and the process proceeds to step S85 (FIG. 7).

That is, when both the reflex action and the deliberate action areactions of specifying a continuous value such as steering angle, anaction may be determined by weighted average using the certainty levelof each action.

It should be noted that both the reflex action determination section 51and the deliberate action determination section 52 determine a pluralityof actions for the plurality of components making up the vehicle bodyaction section 33, and actions that lead to a conflict are also aplurality of actions for the plurality of components. For example, whenone makes an emergency stop to avoid a collision with the obstacleahead, respective actions such as braking and action of taking anavoidance behavior by steering that involve the brake and the steering,are determined. In the case of a discrete action with two options, anexample of which is whether to carry out emergency braking, therefore,an action may be determined by majority decision by using the pluralityof these actions.

When it is decided in step S78 that the resolution mode is not a modethat determines an action by weighted average or majority decision, theprocess proceeds to step S80.

In step S80, the autonomous driving control section 53 decides whetheror not the resolution mode in the event of occurrence of a conflict is aresolution mode that determines an action by using mutual results of thereflex action and the deliberate action. When it is decided in step S80,for example, that the resolution mode is a mode that determines anaction by using mutual results of the reflex action and the deliberateaction, the process proceeds to step S81.

In step S81, the autonomous driving control section 53 determines anaction, determined using mutual results of the reflex action and thedeliberate action, as a determined action, and the process proceeds tostep S85 (FIG. 7).

That is, the reflex action and the deliberate action is an actiondetermined separately. However, if there is a discrepancy between thedecisions of the two, the autonomous driving control section 53controls, for example, the reflex action determination section 51 andthe deliberate action determination section 52 to recalculate the mutualactions by using the results found from the mutual processes asreference values, thereby bringing the two actions into agreement witheach other. Also, the autonomous driving control section 53 controls,for example, the reflex action determination section 51 and thedeliberate action determination section 52 to repeat recalculations forfinding reflex and deliberate actions until a prescribed number ofrepetitions is reached, thereby bringing the two actions into agreementwith each other.

When it is decided in step S80 that the resolution mode is not a modethat determines an action by using mutual results of the reflex actionand the deliberate action, the process proceeds to step S82.

In step S82, the autonomous driving control section 53 decides whetheror not the resolution mode in the event of occurrence of a conflict is aresolution mode that determines an action in accordance with thepriority levels of commands indicating the activation of the reflexaction and the deliberate action. When it is decided in step S82, forexample, that the resolution mode is a mode that determines an action inaccordance with the priority levels of commands indicating theactivation of the reflex action and the deliberate action, the processproceeds to step S83.

In step S83, the autonomous driving control section 53 selects theaction determined in accordance with the priority level of the commandindicating the reflex action and the deliberate action as a determinedaction, and the process proceeds to step S85 (FIG. 7).

That is, commands for emergency braking and so on are defined inadvance, and if that is selected as a reflex action or a deliberateaction, the action is handled with upmost priority. Asuperiority-inferiority relationship may be established between commandsother than emergency commands so that an action is determined based onthe superiority or inferiority of the priority level in the event of aconflict between actions. The superiority or inferiority of commands maybe specified in advance in such a sequence as stop>drive straight aheadwithin lane>deviate from lane>back.

When it is decided in step S82 that the resolution mode is not a modethat determines an action in accordance with the priority level of thecommand indicating the reflex action and the deliberate action, theprocess proceeds to step S84.

In step S84, the autonomous driving control section 53 performs a driverintervention process and resolves the conflict by intervention of thedriver's operation, and determines an action. That is, this case isconsidered a resolution mode that resolves the conflict by accepting thedriver's intervention.

<Driver Intervention Process>

A description will be given here of the driver intervention process withreference to the flowchart depicted in FIG. 9.

In step S101, the autonomous driving control section 53 controls thedisplay section 35 to display the conflicting reflex action anddeliberate action as resolution candidates and display an imageprompting the selection of one of the actions for resolving theconflict.

That is, for example, the conflicting actions, i.e., “a) Maintain Lane”and “b) Change to Right Lane,” are displayed as resolution candidates131 on the right of the mark 124 indicating the occurrence of a conflictin the instrument panel 111 depicted in FIG. 10. “a) Maintain Lane” and“b) Change to Right Lane,” the resolution candidates 131, can beselected by touching the touch panel.

In step S102, the autonomous driving control section 53 decides whetheror not one of the resolution candidates has been selected as a result ofoperation of the operation section 31. When one of “a) Maintain Lane”and “b) Change to Right Lane” in a resolution candidate column 131depicted in FIG. 10 is selected in step S102, the process proceeds tostep S103.

In step S103, the autonomous driving control section 53 selects, of theresolution candidates displayed in the resolution candidate column 131,the action of the selected resolution candidate as a determined action.

On the other hand, when none of the resolution candidates in theresolution candidate column 131 is selected in step S102, the processproceeds to step S104.

In step S104, the autonomous driving control section 53 decides whetheror not autonomous driving mode has been cancelled as a result ofoperation of the operation section 31. When an action is detected thatcorresponds to the expression of intention to cancel autonomous drivingmode such as operation of the selector switch or button displayed on thedisplay section 35 and depression of the brake pedal or the acceleratorpedal, the action is considered a request to cancel autonomous drivingmode, and the process proceeds to step S105.

In step S105, the autonomous driving control section 53 terminatesautonomous driving mode to switch to manual driving mode. As a result ofthis process, a manual driving process will be hereinafter carried outby the manual driving control section 32.

Further, when it is considered in step S104 that no request has beenmade to cancel autonomous driving mode, the process proceeds to stepS106.

In step S106, the autonomous driving control section 53 decides whetheror not a set time period has elapsed after the occurrence of a conflict.When it is considered in step S106 that a set time period has yet toelapse after the occurrence of a conflict, the process returns to stepS101 so that the processes from step S101 to step S106 are repeateduntil the set time period elapses. Then, when it is considered in stepS106 that the set time period has elapsed, the process proceeds to stepS107.

In step S107, the autonomous driving control section 53 considers thatthe resolution mode selects the action of stopping the traveling of themotor vehicle or maintaining the current state as a determined action,thereby selecting the action of stopping the motor vehicle ormaintaining the current state as a determined action. In this case, theresolution mode is considered as stopping the motor vehicle withoutissuing neither a reflex action nor a deliberate action or maintainingthe current state.

That is, if a conflict between a reflex action and a deliberate actioncannot be resolved, or if there is no reflex action or deliberate actionin the command accumulation list, the specified action is selected fromthe stopping action and the current state maintaining action as adetermined action.

That is, if the conflict between the reflex action and the deliberateaction cannot be resolved by the above processes, it is possible todetermine an action by allowing the driver to intervene (allowing thedriver to determine one of the actions or cancel autonomous driving modeto switch to manual driving mode so that the driver drives the vehicleby himself or herself). Also, when there is no driver's intervention,the motor vehicle is stopped, or the current state is maintained,thereby making it possible to safely stop the vehicle or prompt thedriver to drive manually.

We return here to the description of the flowcharts depicted in FIGS. 6and 7.

Because of the processes up to this point, an action is determined byone of the resolution modes specified in advance, making it possible tomaintain autonomous driving mode. On the other hand, if the conflictcannot be resolved in autonomous driving mode, it is possible to promptthe driver to intervene as necessary.

In step S85 (FIG. 7), the autonomous driving control section 53 decideswhether or not the repetitive stopping action within a set time periodis selected as a determined action. When it is decided, for example,that the repetitive stopping action within a set time period is selectedas a determined action, the process proceeds to step S86.

In step S86, the autonomous driving control section 53 displays, forexample, an interface (slide bar IF) image including a slide bar foradjusting parameters that control a threshold and a safety factorrequired to determine a reflex action and a deliberate action on thedisplay section 35, thereby prompting the adjustment of the parametersthat control the threshold and the safety factor. That is, theautonomous driving control section 53 displays, for example, an imagethat includes the slide bar IF as depicted in FIG. 11, thereby promptingthe adjustment of the parameters that control the threshold and thesafety factor. FIG. 11 depicts a mark 151 indicating the occurrence of aconflict appears under the tachometer 122, and a gauge 141 forrepresenting, by a continuous variable, parameters that control thethreshold and the safety factor related to a deliberate action and areflex action, and a slide bar 142 for specifying the parameters thatcontrol the threshold and the safety factor. The slide bar 142 is movedhorizontally in FIG. 11 by touch panel operation and specifies theparameters that control the threshold and the safety factor to match theposition pointed to on the gauge 141.

It should be noted that although an example is described here in whichthe parameters that control the threshold and the safety factor arespecified using the slide bar IF, other parameters may be specified aslong as they can be specified with the slide bar IF. For example, if thereflex action and the deliberate action can be treated with continuousvariables, individually, a weight added to each action and so on may bespecified when an action is determined by weighted average thereof.

In step S87, the autonomous driving control section 53 decides whetheror not the slide bar 142 has been operated horizontally and repeats thesame process until it is considered that the slide bar 142 has beenoperated horizontally. Then, when the slide bar 142 is operated, theprocess proceeds to step S88.

In step S88, the autonomous driving control section 53 finds an actionthat is the weighted average of the deliberate action and the reflexaction in accordance with the weight specified by the slide bar 142 andselects this action that is the weighted average as a determined action.

It should be noted that when the repetitive stopping action within a settime period is not considered a determined action in step S85, theprocesses from step S86 to step S88 are skipped.

That is, the situation in which the repetitive stopping action within aset time period is selected as a determined action is, for example,likely to be an action of passing an oncoming vehicle on a narrow road.At this time, we assume that the deliberate action determines thedirection of travel by referring to global map information, that thereflex action observes the surrounding circumstances, and that the widthof the space around the own vehicle is smaller than the width specifiedby (own vehicle width+margin θ), the stopping action is selected as adetermined action.

Under these circumstances, for example, there is a possibility that, inthe presence of a bicycle parked on the roadside, the determined actionmay be unable to escape from a condition in which the determined actionis a stopping action because of the difficulty in allowing for enoughmargin relative to the own vehicle width. Such a condition is called adeadlock, and as a result of continuing to select safe actions, thestopping action is repeatedly selected as a determined action, and thevehicle ends up remaining in that condition.

By changing the margin θ here using the slide bar 142, it is possiblefor the driver to adjust the motor vehicle behavior while watching thesurrounding situation. To be more specific, the driver can control themotor vehicle by adjusting abstracted adjustment parameters using theslide bar 142 rather than directly controlling the motor vehicle'sbehavior using the accelerator and the wheel.

In general, it is difficult for ordinary drivers to specify theseadjustment parameters properly. However, if the adjustment can be madeusing the slide bar 142 as depicted here, it is easy to deal with thereal world and possible to make adjustment with ease regardless of thedriver.

It should be noted that as an adjustment value that adjustment can bemade easier by decelerating the motor vehicle as the weight specified bythis slide bar 142 deviates from a reference value.

<Improvement for Suppressing the Occurrence of a Conflict>

A description has been given so far of examples for resolving a conflictusing a reflex action and a deliberate action in accordance with aresolution mode specified in advance in the event of occurrence of aconflict. However, it is possible to make the driving control processsmoother by suppressing the occurrence of a conflict itself.

For example, as for margins specified to find a reflex action and adeliberate action, a first value and a second value are specified. Thefirst value contains almost no margin, and the second value containsenough margin, after which first and second reflex actions and first andsecond deliberate actions are found for these values.

Then, an action is determined based on each of the first and secondreflex actions and the first and second deliberate actions, therebymaking it possible to reduce conflicts.

For example, when the reflex action and the deliberate action selecteither a forward-driving action or a stopping action as a determinedaction, a determined action is determined in accordance with acombination of the first and second reflex actions and a combination ofthe first and second deliberate actions.

That is, FIG. 12 vertically depicts combinations of first and secondreflex actions, and horizontally depicts combinations of first andsecond deliberate actions. Also, “G” is a mark that approves aforward-driving action as a determined action based on a combination ofthe first and second reflex actions and a combination of the first andsecond deliberate actions, and “N” is a mark that does not approve aforward-driving action and selects a stopping action as a determinedaction.

That is, if both the first reflex action and the first deliberateaction, both with a small margin, of the combinations of the first andsecond reflex actions and those of the first and second deliberateactions depicted in FIG. 12 approve a forward-driving action (G/X whereX may be N or G), and when the first reflex action is a stopping action,but the second reflex action is a forward-driving action (N/G), and, atthe same time, both the first and second deliberate actions approve aforward-driving action (G/G), or when the first deliberate action is astopping action, but the second deliberate action is a forward-drivingaction (N/G), and, at the same time, both the first and second reflexactions approve a forward-driving action (G/G), a forward-driving action(G) is selected as a determined action.

Conversely, if both the first reflex action and the first deliberateaction, both with a small margin, of the combinations of the first andsecond reflex actions and those of the first and second deliberateactions depicted in FIG. 12 are stopping actions (N/X where X may be Nor G), and when the first reflex action is a forward-driving action, butthe second reflex action is a stopping action (G/N), and, at the sametime, both the first and second deliberate actions approve a stoppingaction (N/N), or when the first deliberate action is a forward-drivingaction, but the second deliberate action is a stopping action (G/N),and, at the same time, both the first and second reflex actions approvea stopping action (N/N), a stopping action (N) is selected as adetermined action.

Then, in such a case, when the combination of the first and secondreflex actions and the combination of the first and second deliberateactions include both forward-driving actions (G/G), and when theyinclude both stopping actions (N/N) (triangles in FIG. 12), a firstconflict condition takes place. On the other hand, when each combinationincludes of a forward-driving action and a stopping action and includesa stopping action and a forward-driving action (squares in FIG. 12), asecond conflict condition takes place.

In such a case, in the first conflict condition, the reflex actions andthe deliberate actions produce opposite results. Therefore, a stoppingaction may be selected. In the second conflict condition, the reflexactions and the deliberate actions produce contradictory results.Therefore, the conflict condition may be resolved through driverintervention.

Also, in each of the first and second conflict conditions depicted inFIG. 12, one of the above seven kinds of conflict resolution modes maybe specified.

Thus, a plurality of reflex actions and a plurality of deliberateactions, each with a different margin, are determined, and actions aredetermined based on a plurality of action patterns. This makes itpossible to reduce the occurrences of conflicts, thereby ensuring smoothdriving control process.

Further, although a description has been given heretofore of a processby which the autonomous driving control section 53 resolves a conflictby one of eight kinds of resolution modes specified in advance todetermine an action, a conflict may be resolved, for example, by aconflict resolution apparatus that is separately realized by an externalserver and cloud computer using a network such as the Internet torealize more rigorous resolution of a conflict.

<Manual Driving Process>

A description will be given next of the manual driving process withreference to the flowchart depicted in FIG. 13.

In step S121, the personalization function learning section 91 of thepersonalization block 22 selects a learning model for learning thepersonalization function of the driver identified by authentication anda storage destination DB (database) in the learning result storagesection 92 to match the driver and the user mode. It should be notedthat if a learning model and a storage destination DB are not registeredin advance in the learning result storage section 92, thepersonalization function learning section 91 creates a newpersonalization function to be learned to match the user mode and thenew storage destination DB.

In step S122, the personalization function learning section 91 acquires,from the detection section 34, detection results detected by varioussensors.

In step S123, the personalization function learning section 91 acquiresoperation information on the driver's driving operation based onoperation signals supplied from the operation section 31. At this time,the manual driving control section 32 acquires the same operationsignals.

In step S124, the personalization function learning section 91 causesthe learning model that matches the habits and customs of the user modeat that time, the driver identified by authentication, to learn thepersonalization function by using operation information acquired fromthe operation section 31 and the detection results acquired from theoperation section 34.

In step S125, the personalization function learning section 91 storesthe personalization function acquired from learning in the learningresult storage section 92 in association with the user mode at thattime, the driver identified by authentication.

In step S126, the manual driving control section 32 supplies, to thevehicle body action section 33 including the components that rendervarious actions of the vehicle body functional, a command that carriesout the associated action based on operation information, therebyactivating the vehicle body action section 33.

As a result of the processes described heretofore, the personalizationfunction is learned to match the user mode based on operationinformation of the operation section 31 operated by the driver anddetection results detected by the detection section 34 and is stored inthe learning result storage section 92. At this time, the manual drivingcontrol section 32 supplies a command associated with operationinformation to the vehicle body action section 33, thereby controllingmanual driving of the motor vehicle.

<Learning of a Personalization Function>

A description will be given here of learning of a personalizationfunction.

We let the detection result (observation value) of the detection section34 at time t be denoted by St, operation information of the driver bedenoted by at, and further the target of the driving operation at thatpoint in time be denoted by gt. Here, when one attempts to directlyimitate the driver's operation, learning is a process of learning thefunction defined by the following formula (1) as a personalizationfunction:

[Math. 1]

a _(t) =f(s _(t) ,g _(t))  (1)

We consider, for example, an action of stopping a motor vehicle. What isanticipated here is that the motor vehicle travels within a given lane,and smoothly decelerates and comes to a stop behind the vehicle in frontor before the white stop line because of red light or other reason.

In this case, some people like to depress the brake pedal early whileothers like to come very close to the vehicle in front, deceleraterapidly, and come to a stop. Further, still others like to keep adistance and stop at his or her desired speed without being affected bythe behavior of the vehicle in front.

The personalization function learning section 91 extracts, fromoperation information making up the driving operation history of thedriver, a piece of operation information that corresponds to the actionof stopping the motor vehicle driven by the driver within a lane andconfigures a set Xstop. The learning problem in this case is expressedby the function depicted as formula (2).

[Math. 2]

a _(t) =f _(stop)(s _(t))  (2)

A function f_(stop) (S_(t)) is a function obtained from detectionresults related to an action of stopping within a lane.

The objective here is to imitate the driver's behavior. Therefore,learning is achieved by realizing the following formula (3):

$\begin{matrix}\lbrack {{Math}.\; 3} \rbrack & \; \\{\min {\sum\limits_{{({s_{i},a_{i}})} \in X_{stop}}{f_{diff}( {a_{i},{f_{stop}( s_{i} )}} )}}} & (3)\end{matrix}$

The following formula (4), for example, can be used as an errorfunction:

[Math. 4]

f _(diff)(a ₁ ,a ₂)≡∥a ₁ −a ₂∥²  (4)

Then, learning by function approximation is carried out that makes anoutput value of a machine represented by the following formula (5)approach an instructor signal ai with respect to history data Xstopincluding operation information at the time of stopping within a lane.

[Math. 5]

a _(i) =f _(stop)(s _(i))  (5)

A learner called Deep Learning based on multi-layered feedforward neuralnetwork, for example, can be used as a learner. For more informationabout learning with Deep Learning, “Machine Learning ProfessionalSeries: Deep Learning (Takayuki Okaya, Kodansha Scientific),” forexample, should be referred to. Naturally, not only this but also anarbitrary function approximator may be used.

It should be noted that the operation information at may be learned withthe detection result St in a given condition by inverse reinforcementlearning using the driver's driving operation as an instructor signal.

Also, data other than the above may be used for learning, and forexample, information about the driver, information about passengers,information about in-vehicle environment, information about out-vehicleenvironment, information about motor vehicle's traveling plan, and so onmay be used.

Here, specific information about the driver may include one or aplurality of pieces of information from among driver's vital information(e.g., heart rate, pulse, blood pressure, temperature, blood sugarlevel, breath alcohol concentration, blood alcohol concentration, bloodoxygen concentration, awakeness level, concentration level, feeling,emotion, brain wave), and information about the driver's attitude, lineof sight, body motion information, and so on, movements, and behavioralstate.

Also, information about passengers may include one or a plurality ofpieces of information from among number of passengers, ages, sexes, seatpositions, usage condition of safety apparatuses such as seat belts,fellow passenger vital information (e.g., heart rate, pulse, bloodpressure, temperature, blood sugar level, breath alcohol concentration,blood alcohol concentration, blood oxygen concentration, awakenesslevel, concentration level, feeling, emotion, brain wave), andinformation about the driver's attitude, line of sight, body motioninformation, and so on, movements, and behavioral state.

Further, information about in-vehicle environment may include one or aplurality of pieces of information from among in-vehicle (at driver'sseat, assistant driver's seat, and each passenger's seat) environmentmeasured values (e.g., temperature, humidity, air flow, vibration,noise, illuminance, oxygen concentration), data of sensors mounted tothe target motor vehicle, real-time information related to motorvehicle's motion, motor vehicle's position, traveling direction (andmeasurement accuracy thereof), motor vehicle's speed, angular speed,acceleration, and angular acceleration (and measurement accuracythereof), operation values in connection with the accelerator, brake,and steering, operation information of turn signals, windshield wipers,and other mounted equipment, activation states of safety apparatusessuch as ABS (Antilock Brake System), TCS (Traction Control System), LKAS(Lane Keep Assist System), and ACC (Adaptive Cruise Control), andfailure-related information or warning information and errorinformation.

Also, information about out-vehicle environment may include one or aplurality of pieces of information from among positions, travelingdirections, speeds, angular speeds, accelerations, and angularaccelerations (and measurement accuracy thereof) of surrounding nearbymotor vehicles (including motorcycles), operational states of brakelamp, turn signals, hazard lamp of surrounding nearby motor vehicles(including motorcycles), V2V (Vehicle to Vehicle) communication datafrom surrounding nearby motor vehicles (including motorcycles),positions, traveling directions, speeds, angular speeds, accelerations,and angular accelerations (and measurement accuracy thereof) ofsurrounding light motor vehicles, positions, traveling directions,speeds, angular speeds, accelerations, and angular accelerations (andmeasurement accuracy thereof) of surrounding pedestrians, states oftraffic lights in surrounding area, and in particular, states of thoseahead, information about accidents, construction works, lane closures,or the like on the roads to be travelled by the motor vehicle inquestion, V2X (Vehicle to X (X: Everything)) communication data fromsurrounding pedestrians or out-vehicle infrastructure, and climate andweather information in the area to be travelled by the motor vehicle inquestion.

Further, information about traveling plan of the motor vehicle inquestion may include one or a plurality of pieces of information fromamong origin and departure time, or destination (a plurality ofcandidates thereof), or area scheduled to be traveled, current locationand current time, and traveling (scheduled) route from origin todestination (candidate).

<Personalization Function Updating Process>

A description will be given next of the personalization functionupdating process with reference to the flowchart depicted in FIG. 14.

The personalization function updating process is generally carried outafter the end of the driving control process as described with referenceto FIG. 2. However, the personalization function updating process may becarried out at other timing as long as the driving control process isnot in progress.

In step S141, the learning result verification section 93 reads apersonalization function stored in the learning result storage section92. When there are a plurality of personalization functions or whenthere is a personalization function for each of a plurality of usermodes, the learning result verification section 93 reads these functionsindividually.

In step S142, the learning result verification section 93 supplies theread personalization function to the verification apparatus 13 via anetwork, typically the Internet, and requests verification. As a resultof this process, the verification apparatus 13 carries out averification process, thereby verifying whether or not there is anyproblem with the action of the personalization function such as safety.It should be noted that the verification process will be described laterwith reference to FIG. 15 onward.

In step S143, the verification result decision section 94 acquires theverification result from the verification apparatus 13.

In step S144, the verification result decision section 94 decides, basedon a verification result, whether or not the corrected action using thepersonalization function has realized problem-free driving in a virtualspace. In step S144, when it is considered, for example, that thecorrected action using the personalization function has realizedproblem-free driving in a virtual space, the process proceeds to stepS145.

In step S145, the verification result decision section 94 notifies thepersonalization function updating section 95 that the action of thecorrected command using the personalization function has realizedproblem-free driving. As a result of this notice, the personalizationfunction updating section 95 updates the personalization function of theassociated driver and the associated user mode that is stored in thepersonalization function storage section 54 with the personalizationfunction that has undergone learning to a problem-free level and that isstored in the learning result storage section 92.

It should be noted that, in step S144, when it is considered, forexample, that the action of the corrected command using thepersonalization function has failed to realize problem-free driving, theprocess in step S145 is skipped, and the personalization function is notupdated. Also, when there are personalization functions for a pluralityof drivers, or when there is a personalization function specified foreach of a plurality of user modes, each personalization function issubjected to the verification process and updated individually dependingon the verification result.

That is, as a result of the processes described heretofore, apersonalization function is found for each driver and for each user modeby learning. Further, the verification process is carried outindividually. When there is no problem with the autonomous drivingprocess carried out by the corrected action corrected by using apersonalization function for each, the personalization function iscorrected.

As a consequence, of the personalization functions learned in such amanner as to reflect driving-related habits and customs of the driver inmanual driving mode, only those considered error-free by theverification process are updated.

As a result, even in autonomous driving mode, it is possible to safelyrealize autonomous driving control that reflects driving habits andcustoms of the target driver in manual driving mode for each driver andfor each driver's user mode.

Also, in the case of a neural network, personalization functions such asnetwork weights are updated to those that have undergone learning. Ingeneral, “dictionary data” for calculating the operation information atfor the detection result St is updated. However, the calculationalgorithm itself may be changed so that the execution code itself of thefunction for calculating the operation information at as an outputresult by using the detection result St as an input is replaced.

<Configuration Example of the Verification Apparatus>

A description will be given next of a configuration example of theverification apparatus 13 with reference to the block diagram depictedin FIG. 15.

The verification apparatus 13 is designed to verify safety and otherfactors of the personalization function whose verification has beenrequested by the driving control apparatus 11. To be more specific, theverification apparatus 13 virtually reproduces simulated driving of amotor vehicle equipped with the driving control apparatus 11 in avirtual space in autonomous driving mode using a personalizationfunction, thereby confirming the presence or absence of defects such asaccidents and verifying safety and other factors of the personalizationfunction.

More specifically, the verification apparatus 13 includes anorigin/destination random setup section 181, a route generation section182, a checkpoint position calculation section 183, a behaviordetermination model calculation section 184, a simulator 185, an eventgeneration section 186, a state calculation section 187, a sensormodel/noise model generation section 188, a recording section 189, and averification section 190.

The origin/destination random setup section 181 randomly specifies anorigin and a destination in a virtual space and supplies them to theroute generation section 182 and the state calculation section 187.

The route generation section 182 specifies a route from the origin andthe destination specified by the origin/destination random setup section181 and supplies the route to the checkpoint position calculationsection 183.

The checkpoint position calculation section 183 calculates a nextcheckpoint on the generated route and specifies the driving operationtarget ‘gt’ at the checkpoint. The checkpoint here refers, for example,to a point where a state is calculated and a behavior is determined onthe route map depicted in FIG. 16. In FIG. 16, the positions depicted byblack dots on a route r specified along a road R drawn in the map arecheckpoints c1 to cn. Then, the next driving operation target ‘gt’ isspecified for each of these checkpoints c1 to cn.

Among specific examples of the driving operation target ‘gt’ are“relative position and relative attitude angle of next checkpoint(relative to own vehicle),” “speed and acceleration profile when passingcheckpoint,” and “curvature of route scheduled to be travelled (atcheckpoint).” In the stop scene, for example, the speed and theacceleration are 0 (at the stop line) 100 m ahead with the car orientedin the same direction as now.

The sensor model/noise model generation section 188 builds varioussensor models making up the detection section 34, generates a noisemodel for each sensor, and supplies them to the state calculationsection 187.

The state calculation section 187 calculates, as a state ‘St,’ adetection result (observation value) likely to be detected by thedetection section 34 based on the traveling position in a virtual spacesupplied from the simulator 185, event information such as someonerushing out and weather change supplied from the event generationsection 186, and sensor model and noise model information supplied fromthe sensor model/noise model generation section 188.

More specifically, the state ‘St’ is a virtual detection result of thedetection section 34 mounted to the motor vehicle equipped with thedriving control apparatus 11 and that has learned a personalizationfunction. The state ‘St’ is, for example, a “millimeter wave radar” andan “image captured by a stereo camera” or “positions, travelingdirections, speeds, angular speeds, accelerations, and angularaccelerations of surrounding nearby motor vehicles” and “position,traveling direction, speed, angular speed, acceleration, and angularacceleration of motor vehicle.” Also, the detection result may bevarious kinds of information in addition to the above, and it ispossible to contribute to “personalization” by using various kinds ofinformation. For example, it is possible to reflect driving-relatedhabits and customs on highways and common roads and at daytime andnighttime.

It should be noted that, as for the origin for which the traveling stateis reproduced by the simulator 185, information supplied from theorigin/destination random setup section 181 is used.

The behavior determination model calculation section 184 determines abehavior determination model ‘at’ using the personalization functionsupplied from the verification section 190 and whose verification hasbeen requested based on the driving operation target ‘gt’ at thecheckpoint supplied from the checkpoint position calculation section 183and the state ‘St’ supplied from the state calculation section 187. Thebehavior determination model calculation section 184 supplies thebehavior determination model ‘at’ to the simulator 185. This behaviordetermination model ‘at’ corresponds to driver's operation informationdescribed above.

The simulator 185 reproduces the traveling (action) of the motor vehicleto which the driving control apparatus 11 is mounted in a virtual spacebased on the behavior determination model ‘at’ supplied from thebehavior determination model calculation section 184 and supplies theresult thereof to the event generation section 186, the statecalculation section 187, and the recording section 189. The action inthe virtual space found by the simulator 185 is theoretically the actionitself of the motor vehicle determined by the autonomous driving controlblock 21.

The event generation section 186 generates events by using the resultsof the actions at the checkpoints, successively supplied from thesimulator 185, as triggers and supplies the events to the statecalculation section 187 and the recording section 189.

The recording section 189 records the simulation results supplied fromthe simulator 185 and various events supplied from the event generationsection 186 in association with each other for each checkpoint. That is,the recording section 189 successively records the verification resultsof the motor vehicle to which the driving control apparatus 11 ismounted in the virtual space while this verification process is inprogress.

The verification section 190 accepts a personalization function suppliedfrom the driving control apparatus 11 and whose verification has beenrequested and supplies the accepted personalization function to thebehavior determination model calculation section 184. Also, theverification section 190 reads the verification results recorded in therecording section 189 and supplies the results to the driving controlapparatus 11 in association with the personalization function whoseverification has been requested.

<Verification Process>

A description will be given next of the verification process handled bythe verification apparatus 13 depicted in FIG. 15 with reference to theflowchart depicted in FIG. 17.

In step S161, the verification section 190 decides whether or not thedriving control apparatus 11 has sent a request for verification of apersonalization function via a network and repeats the same processuntil a request is made. For example, when a request is sent togetherwith a personalization function as a result of the process in step S142depicted in FIG. 14, the process proceeds to step S162.

In step S162, the verification section 190 acquires a personalizationfunction sent and supplies the function to the behavior determinationmodel calculation section 184.

In step S163, the origin/destination random setup section 181 randomlyspecifies an origin and a destination in the virtual space in thesimulator 185 and supplies them to the route generation section 182 andthe state calculation section 187.

In step S164, the route generation section 182 generates a route basedon the origin and destination randomly specified by theorigin/destination random setup section 181 and supplies the route tothe checkpoint position calculation section 183.

In step S165, the checkpoint position calculation section 183calculates, based on the route supplied, the position of the nextcheckpoint on the route, specifies the driving operation target ‘gt,’and supplies the target to the behavior determination model calculationsection 184.

In step S166, the state calculation section 187 specifies a departuretime and an origin in the simulator 185.

In step S167, the sensor model/noise model generation section 188generates sensor model and noise model information and supplies theinformation to the state calculation section 187.

In step S168, the state calculation section 187 calculates the state‘St’ based on the current time, position, and sensor model and noisemodel information in the simulator 185 and supplies the state to thebehavior determination model calculation section 184. It should be notedthat when an event is generated by the event generation section 186which will be described later, the state ‘st’ is calculated inconsideration of the event generated.

In step S169, the behavior determination model calculation section 184calculates the behavior determination model ‘at’ using thepersonalization function whose verification has been requested andsupplies the model to the simulator 185. To be more specific, in thecase of a personalization function f whose verification has beenrequested, the behavior determination model calculation section 184calculates the behavior determination model ‘at’ (=f(st, gt)) byinputting information of the state ‘St’ and the driving operation target‘gt’ to the personalization function f.

In step S170, the simulator 185 carries out physical simulation andsupplies the simulation result to the event generation section 186, thestate calculation section 187, and the recording section 189. That is,the simulator 185 reproduces a traveling state in the virtual space thattakes place when the motor vehicle to which the driving controlapparatus 11 is mounted undergoes the driving operation identified bythe behavior determination model ‘at.’

In step S171, the event generation section 186 generates an event thatmatches the behavior of the motor vehicle to which the driving controlapparatus 11 is mounted in the virtual space supplied from the simulator185. The event generation section 186 supplies the event to the statecalculation section 187 and the recording section 189.

In step S172, the recording section 189 records the event generated bythe event generation section 186 and the simulation result of thesimulator 185 in association with the checkpoint.

In step S173, the verification section 190 decides whether or not theverification is over. The end of the verification process is specified,for example, by the duration of simulation and arrival time at thedestination. When the verification is not over in step S173, the processproceeds to step S174.

In step S174, the checkpoint position calculation section 183 calculatesthe position of the next checkpoint, specifies the driving operationtarget ‘gt’ at that checkpoint, and supplies the target to the behaviordetermination model calculation section 184, and the process returns tostep S167.

That is, the processes from step S167 to step S174 are repeated untilthe verification process is over.

Then, when it is considered in step S173 that the verification is over,the process proceeds to step S175.

In step S175, the verification section 190 generates a verificationresult based on the simulation result recorded in the recording section189.

In step S176, the verification section 190 supplies the generatedverification result to the driving control apparatus 11.

Because of the above process, it is possible to verify safety when theautonomous driving process is performed by a personalization function.It should be noted that when the verification result is sent to thedriving control apparatus 11, the personalization function is updatedonly when there are no accidents and no problems as a result of theprocesses from step S143 onward in FIG. 14.

It should be noted that motor vehicle's action modes such as “travelingon highway,” “traveling on common road (lane),” “passing intersection,”“stopping/decelerating,” “traveling in non-lane area (parking area),”“making U-turn,” and “parked on road shoulder” may be added as thedriving operation target ‘gt’ and the state ‘St.’ This may facilitatepersonalization function learning.

Also, although an example has been described above in which theverification apparatus 13 is configured as an external apparatus via anetwork, typically, the Internet, the verification apparatus 13 may beprovided in the driving control apparatus 11 by reinforcing the hardwarefunction.

2. First Modification Example

Although an example has been described above in which only averification result found by the verification process is supplied fromthe verification apparatus 13 to the driving control apparatus 11,failure data that resulted, for example, in an accident duringsimulation and correct data that can avoid accidents may be supplied tothe driving control apparatus 11 together with a verification result. Asa result, the driving control apparatus 11 can realize relearningbecause of feedback of failure data and correct data.

<Configuration Example of the Verification Apparatus in the FirstModification Example>

A description will be given next of a configuration example of theverification apparatus 13 that supplies not only a verification resultbut also failure data and correct data to the driving control apparatus11 with reference to the block diagram depicted in FIG. 18. It should benoted that the components in FIG. 18 having the same functions as thoseof the verification apparatus 13 depicted in FIG. 15 are denoted by thesame names and the same reference numerals, and the description thereofwill be omitted. That is, the verification apparatus 13 depicted in FIG.18 differs from the verification apparatus 13 depicted in FIG. 15 inthat a verification section 201 is provided rather than the verificationsection 190.

The verification section 201 has the same basic functions as theverification section 190 and further supplies not only a verificationresult but also failure data and correct data to the driving controlapparatus 11 if there is a problem with the verification result of thepersonalization function.

<Configuration Example of the Driving Control Apparatus in the FirstModification Example>

A description will be given next of a configuration example of thedriving control apparatus 11 that receives not only a verificationresult but also failure data and correct data from the verificationapparatus 13. It should be noted that the components in FIG. 19 havingthe same functions as those of the driving control apparatus 11 depictedin FIG. 1 are denoted by the same names and the same reference numerals,and the description thereof will be omitted.

That is, the driving control apparatus 11 depicted in FIG. 19 differsfrom the driving control apparatus 11 depicted in FIG. 1 in that apersonalization function learning section 211 and a learning resultverification section 212 are provided rather than the personalizationfunction learning section 91 and the learning result verificationsection 93.

The learning result verification section 212 basically has the samefunctions as the learning result verification section 93 and furtherreceives a verification result, failure data, and correct data sent fromthe verification apparatus 13 depicted in FIG. 19. At this time, whenfailure data and correct data are received together with a verificationresult indicating that there is a problem with the personalizationfunction whose verification has been requested, the learning resultverification section 212 feeds the failure data and the correct databack to the personalization function learning section 211.

The personalization function learning section 211 basically has the samefunctions as the personalization function learning section 91 andfurther uses the failure data and the correct data hereafter forfunction learning when these pieces of data are received from thelearning result verification section 212.

<Verification Process Handled by the Verification Apparatus Depicted inFIG. 18>

A description will be given here of the verification process handled bythe verification apparatus 13 in FIG. 18 for sending not only averification result but also failure data and correct data to thedriving control apparatus 11 with reference to the flowchart depicted inFIG. 20. It should be noted that because the processes from step S201 tostep S215 and that in step S217 in FIG. 20 are the same as those fromstep S161 to step S176 in FIG. 17, the description thereof will beomitted.

That is, in step S216, the verification section 201 decides whether ornot there is any problem with the verification result. Here, if there isa problem with the verification result, the process proceeds to stepS218.

In step S218, the verification section 201 supplies not only theverification result but also failure data and correct data to thedriving control apparatus 11.

As a result of the above process, it is possible to supply not only averification result but also failure data and correct data to thedriving control apparatus 11 if there is a problem with apersonalization function.

<Personalization Function Updating Process Handled by the DrivingControl Apparatus 11 Depicted in FIG. 19>

A description will be given next of the personalization functionupdating process handled by the driving control apparatus 11 in FIG. 19to which not only a verification result but also failure data andcorrect data are sent with reference to the flowchart depicted in FIG.21. It should be noted that because the processes in steps S241, S242,S244, and S245 in FIG. 19 are the same as those in steps S141, S142,S144, and S145 in FIG. 14, the description thereof will be omitted asappropriate.

That is, in step S243, the learning result verification section 212acquires failure data and correct data together with a verificationresult.

Then, in step S244, if there is a problem with the personalizationfunction, the process proceeds to step S246.

In step S246, the learning result verification section 212 supplies thefailure data and the correct data to the personalization functionlearning section 211 for feedback.

The above process allows for learning by the learning resultverification section 212 using the failure data and the correct data,thereby realizing relearning. It should be noted that failure data isrequired for relearning. Therefore, correct data is not essential.

3. Second Modification Example

Although a description has been given above of an example of theverification apparatus 13 that causes the driving control apparatus 11to send not only a verification result but also failure data and correctdata, the updating of a personalization function may be facilitated bysubjecting a personalization function to retraining through simulationin the verification apparatus 13 and sending the personalized functionback to the driving control apparatus 11 as a corrected function ifthere is a problem with the personalization function. This makes itpossible to receive a corrected function and realize early updating evenif a perfect personalization function cannot be achieved by the drivingcontrol apparatus 11 by learning.

<Configuration Example of the Verification Apparatus in the SecondModification Example>

A description will be given next of a configuration example of theverification apparatus 13 that generates a corrected function bycorrecting a personalization function whose verification result has beenfound to be problematic by retraining and supplies not only averification result but also failure data and correct data to thedriving control apparatus 11. It should be noted that the components inFIG. 22 having the same functions as those of the verification apparatus13 depicted in FIG. 18 are denoted by the same names and the samereference numerals, and the description thereof will be omitted.

That is, the verification apparatus 13 depicted in FIG. 22 differs fromthe verification apparatus 13 depicted in FIG. 18 in that a verificationsection 221 is provided rather than the verification section 201.

The verification section 221 has the same basic functions as theverification section 201 and further generates a corrected function bysubjecting a personalization function to retraining (relearning) ifthere is a problem with the verification result of the personalizationfunction, and supplies not only a verification result but also failuredata and correct data to the driving control apparatus 11. At this time,the verification section 221 subjects the corrected function to theverification process in the same manner as for the personalizationfunction and sends the verification result to the driving controlapparatus 11. In this case, therefore, the verification section 221sends failure data and correct data to the driving control apparatus 11together with two kinds of verification results, one for thepersonalization function whose verification has been requested andanother for the corrected function.

<Configuration Example of the Driving Control Apparatus in the FirstModification Example>

A description will be given next of a configuration example of thedriving control apparatus 11 for receiving not only verification resultsbut also failure data, correct data, and a corrected function from theverification apparatus 13 with reference to FIG. 23. It should be notedthat the components in FIG. 23 having the same functions as those of thedriving control apparatus 11 depicted in FIG. 19 are denoted by the samenames and the same reference numerals, and the description thereof willbe omitted.

That is, the driving control apparatus 11 depicted in FIG. 23 differsfrom the driving control apparatus 11 depicted in FIG. 19 in that apersonalization function learning section 231, a learning resultverification section 232, and a verification result decision section233, and a personalization function updating section 234 rather than thepersonalization function learning section 211, the learning resultstorage section 212, the verification result decision section 94, andthe personalization function updating section 95.

The learning result verification section 232 basically has the samefunctions as the learning result storage section 212 and furtherreceives verification results, failure data, correct data, and acorrected function sent from the verification apparatus 13 depicted inFIG. 22. At this time, when failure data, correct data, and a correctedfunction are received together with verification results indicating thatthere is a problem with the personalization function whose verificationhas been requested, the learning result verification section 232 feedsthe failure data, the correct data, and the corrected function back tothe personalization function learning section 231.

The personalization function learning section 231 basically has the samefunctions as the personalization function learning section 211 andfurther uses the failure data, the correct data, and the correctedfunction hereafter for function learning when these pieces of data andthe function are acquired from the learning result verification section232.

Further, the verification result decision section 233 basically has thesame functions as the verification result decision section 94 andfurther makes a decision as to updating of the personalization functionbased on the verification result of a corrected function when acorrected function is sent together, and updates the personalizationfunction with the corrected function when there is no problem with theverification result.

The personalization function updating section 234 basically has the samefunctions as the personalization function updating section 95 andfurther updates the associated personalization function stored in thepersonalization function storage section 54 with the corrected functionwith the corrected function when there is no problem with theverification result of the corrected function.

<Verification Process Handled by the Verification Apparatus Depicted inFIG. 22>

A description will be given here of the verification process forgenerating a corrected function obtained by correcting a personalizationfunction by retraining if there is a problem with a verification resultwith reference to the flowchart depicted in FIG. 24. It should be notedthat because the processes in steps S261 to S275 and step S277 in FIG.20 are the same as those in steps S161 to S176 in FIG. 17, thedescription thereof will be omitted as appropriate.

That is, in step S276, the verification section 221 decides whether ornot there is any problem with the verification result. Here, if there isa problem with the verification result, the process proceeds to stepS278.

In step S278, the verification section 221 corrects the personalizationfunction by subjecting it to retraining (relearning), generates acorrected function, and further verifies the corrected function.

In step S279, the verification section 190 supplies failure data and thecorrected function to the driving control apparatus 11 together with theverification result of the corrected function.

It should be noted that there is a possibility that the correctedfunction may not necessarily reach a safe level depending on the amountof learning. However, a state is created in which learning required toachieve a perfect corrected function is performed to a certain extent.Therefore, it is possible to improve learning efficiency by takingadvantage of the corrected function.

As a result of the above process, it is possible to supply not only averification result but also failure data and a corrected function tothe driving control apparatus 11.

<Personalization Function Updating Process Handled by the DrivingControl Apparatus Depicted in FIG. 23>

A description will be given next of the personalization functionupdating process handled by the driving control apparatus 11 whenfailure data and a corrected function are sent together with averification result with reference to the flowchart depicted in FIG. 25.It should be noted that because the processes in steps S301, S302, S304,and S305 in FIG. 21 are the same as those in steps S141, S142, S144, andS145 in FIG. 14, the description thereof will be omitted as appropriate.

That is, in step S303, the learning result verification section 232acquires failure data and a corrected function together with averification result.

Then, in step S304, if the verification result decision section 233decides that there is a problem with the personalization function, theprocess proceeds to step S306.

In step S306, the verification result decision section 233 decideswhether or not there is a problem with the corrected function. If it isdecided in step S306 that there is a problem, the process proceeds tostep S307.

In step S307, the learning result verification section 232 supplies thefailure data and the corrected function to the personalization functionlearning section 231 for feedback.

The above process allows for relearning. Further, learning is advancedto a certain extent, thereby making it possible to improve learningefficiency.

On the other hand, in step S306, when there is no problem with thecorrected function, the process proceeds to step S305. That is, in thiscase, in step S305, the personalization function updating section 234updates the associated personalization function stored in thepersonalization function storage section 54 with the corrected functionsent.

As a result of the above process, if there is a problem with thepersonalization function following the verification by the verificationapparatus 13, a corrected function is found by retraining. When there isno problem with the corrected function found, the driving controlapparatus 11 can update the personalization function immediately.

Also, even when the corrected function is not perfect, it is possible tosubject the function to relearning using a corrected function whoselearning is advanced to a certain extent and failure data, therebyallowing for improved learning efficiency.

4. First Application Example

The technology according to the present disclosure is applicable to avariety of products. For example, the technology according to thepresent disclosure may be realized as an apparatus mounted to one ofmotor vehicle, electric vehicle, hybrid electric vehicle, motorcycle,and so on.

FIG. 26 is a block diagram illustrating a schematic configuration of amotor vehicle control system 2000 to which the technology according tothe present disclosure is applicable. The motor vehicle control system2000 includes a plurality of electronic control units connected via acommunication network 2010. In the example depicted in FIG. 26, themotor vehicle control system 2000 includes a drive-related control unit2100, a body-related control unit 2200, a battery control unit 2300,out-vehicle information detection unit 2400, an in-vehicle informationdetection unit 2500, and an integrated control unit 2600. Thecommunication network 2010 that connects the plurality of these controlunits may be an on-vehicle communication network such as CAN (ControllerArea Network), LIN (Local Interconnect Network), LAN (Local AreaNetwork) and FlexRay (registered trademark) compliant with an arbitrarystandard.

Each control unit includes a microcomputer, a storage section, and adrive circuit. The microcomputer handles operations according to avariety of programs. The storage section stores programs executed by themicrocomputer or parameters used for various operations, and so on. Thedrive circuit drives various apparatuses to be controlled. Each controlunit includes not only a network I/F for communication with othercontrol units via the communication network 2010 but also acommunication I/F for communication with in- and out-vehicle apparatusesor sensors in a wired or wireless fashion. In FIG. 26, a microcomputer2610, a general-purpose communication I/F 2620, a dedicatedcommunication I/F 2630, a positioning section 2640, a beacon receptionsection 2650, an in-vehicle apparatus I/F 2660, an audio/video outputsection 2670, an on-vehicle network I/F 2680, and a storage section 2690are depicted as functional components of the integrated control unit2600. Other control units similarly include a microcomputer, acommunication I/F, a storage section, and so on.

The drive-related control unit 2100 controls the action of thedrive-related apparatuses of the motor vehicle in accordance withvarious programs. For example, the drive-related control unit 2100functions as a control apparatus of a driving force generating apparatusfor generating a driving force of a motor vehicle such as internalcombustion engine and drive motor, a driving force transmissionmechanism for transmitting a driving force to the wheels, a steeringmechanism for adjusting the steering angle of a motor vehicle, and Zc afor generating a braking force of a motor vehicle. The drive-relatedcontrol unit 2100 may also have functions as a control apparatus such asABS (Antilock Brake System) or an ESC (Electronic Stability Control).

A vehicle state detection section 2110 is connected to the drive-relatedcontrol unit 2100. The vehicle state detection section 2110 includes,for example, at least one of a gyrosensor for detecting the angularspeed of axial rotational motion of a vehicle body, an accelerationsensor for detecting the acceleration of a motor vehicle, and a sensorfor detecting the amount of depression of the accelerator pedal, theamount of depression of the brake pedal, the steering angle of thesteering wheel, engine revolutions per minute, wheel rotational speed,and so on. The drive-related control unit 2100 performs operations usingsignals input from the vehicle state detection section 2110, therebycontrolling the internal combustion engine, the drive motor, theelectric power steering apparatus, or the brake apparatus.

The body-related control unit 2200 controls the action of variousapparatuses provided on the vehicle body in accordance with variousprograms. For example, the body-related control unit 2200 functions as acontrol apparatus of a keyless entry system, a smart key system, and apower window apparatus or various lamps such as headlights, rear lights,brake lamp, turn signals, or fog lamp. In this case, radio waves emittedfrom a portable transmitter that replaces a key or various switchsignals can be input to the body-related control unit 2200. Thebody-related control unit 2200 accepts these radio wave and signalinputs and controls the motor vehicle's door lock apparatus, powerwindow apparatus, lamps, and so on.

The battery control unit 2300 controls a secondary battery 2310, a powersupply source of the drive motor, in accordance with various programs.For example, battery temperature, battery output voltage, remainingbattery charge, or other information is input to the battery controlunit 2300 from a battery apparatus having the secondary battery 2310.The battery control unit 2300 performs arithmetic processing using thesesignals, thereby controlling temperature control over the secondarybattery 2310, a cooling apparatus provided on the battery apparatus, orother apparatus.

The out-vehicle information detection unit 2400 detects informationoutside a motor vehicle equipped with the motor vehicle control system2000. For example, at least one of an imaging section 2410 and anout-vehicle information detection section 2420 is connected to theout-vehicle information detection unit 2400. The imaging section 2410includes at least one of a ToF (Time Of Flight) camera, a stereo camera,a monocular camera, an infrared camera, and other cameras. Theout-vehicle information detection section 2420 includes, for example, anenvironment sensor that detects current weather or climate or asurrounding information detection sensor that detects other vehicles,obstacles, pedestrians, or others around the motor vehicle equipped withthe motor vehicle control system 2000.

The environment sensor may be, for example, one of a rain drop sensorthat detects rainy weather, a fog sensor that detects fog, a sunlightsensor that detects sunlight level, and a snow sensor that detectssnowfall. The surrounding information detection sensor may be one of anultrasonic sensor, a radar apparatus, and an LIDAR (Light Detection andRanging, Laser Imaging Detection and Ranging) apparatus. These imagingsection 2410 and out-vehicle information detection section 2420 may beincluded as separate sensors or apparatuses or as an integratedapparatus included a plurality of sensors or apparatuses.

Here, FIG. 27 illustrates examples of installation positions of theimaging section 2410 and the out-vehicle information detection section2420. Imaging sections 2910, 2912, 2914, 2916, and 2918 are provided, atleast one on a front nose, side mirrors, a rear bumper, a back door, anda top of a front glass in a compartment. The imaging section 2910provided on the front nose and the imaging section 2918 provided on thetop of the front glass in the compartment acquire mainly front images ofa motor vehicle 2900. The imaging sections 2912 and 2914 provided on theside mirrors acquire mainly side images of the motor vehicle 2900. Theimaging sections 2916 provided on the rear bumper or the back dooracquire mainly rear images of the motor vehicle 2900. The imagingsection 2918 provided on the top of the front glass in the compartmentis used mainly to detect motor vehicles ahead, pedestrians, obstacles,traffic lights, traffic signs, or driving lanes.

It should be noted that FIG. 27 illustrates examples of imaging rangesof the imaging sections 2910, 2912, 2914, and 2916. An imaging range ‘a’depicts the imaging range of the imaging section 2910 provided on thefront nose. Imaging ranges ‘b’ and ‘c’ depict the imaging ranges of theimaging sections 2912 and 2914 provided on the side mirrors. An imagingrange ‘d’ depicts the imaging range of the imaging section 2916 providedon the rear bumper or the back door. For example, superimposing imagedata, captured by the imaging sections 2910, 2912, 2914, and 2916, oneon top of the other, provides a bird's eye view image as seen from abovethe motor vehicle 2900.

Out-vehicle information detection sections 2920, 2922, 2924, 2926, 2928,and 2930 provided on the front, the rear, the sides, corners, and on thetop of the front glass in the compartment of the motor vehicle 2900 maybe, for example, ultrasonic sensors or radar apparatuses. Theout-vehicle information detection sections 2920, 2926, and 2930 providedon the front nose, the rear bumper, the back door, and on the top of thefront glass in the compartment of the motor vehicle 2900 may be, forexample, LIDAR apparatuses. These out-vehicle information detectionsections 2920 to 2930 are used mainly to detect motor vehicles ahead,pedestrians, obstacles, or others.

A description will continue with reference back to FIG. 26. Theout-vehicle information detection unit 2400 causes the imaging section2410 to capture images outside the vehicle and receives captured imagedata. Also, the out-vehicle information detection unit 2400 receivesdetection information from the connected out-vehicle informationdetection section 2420. When the out-vehicle information detectionsection 2420 is an ultrasonic sensor, a radar apparatus, or an LIDARapparatus, the out-vehicle information detection unit 2400 causes anultrasonic wave, an electromagnetic wave, or other wave to be emittedand receives information about a received reflected wave. Theout-vehicle information detection unit 2400 may perform an objectdetection process for detecting persons, vehicles, obstacles, signs,characters on the road, or others or a distance detection process basedon the received information. The out-vehicle information detection unit2400 may perform an environment recognition process for detectingrainfall, fog, road surface condition or others based on the receivedinformation. The out-vehicle information detection unit 2400 maycalculate a distance to an object outside the vehicle based on thereceived information.

Also, the out-vehicle information detection unit 2400 may perform anobject recognition process for recognizing persons, vehicles, obstacles,signs, characters on the road, or others or a distance detection processbased on the received information. The out-vehicle information detectionunit 2400 may generate a bird's eye view image or a panoramic image byperforming distortion correction, position alignment, or other processon the received image data and combine the data with image data capturedby the different imaging section 2410. The out-vehicle informationdetection unit 2400 may perform a viewpoint conversion process usingimage data captured by the different imaging section 2410.

The in-vehicle information detection unit 2500 detects in-vehicleinformation. For example, a driver state detection section 2510 thatdetects the driver's state is connected to the in-vehicle informationdetection unit 2500. The driver state detection section 2510 may be acamera that images the driver, a biological sensor that detectsbiological information of the driver, a microphone that collects audioin the compartment, or other apparatus. A biological sensor is provided,for example, on a seat surface, the steering wheel, or other location todetect biological information of a passenger sitting on the seat or thedriver holding the steering wheel. The in-vehicle information detectionunit 2500 may calculate fatigue level or concentration level of thedriver based on detection information input from the driver statedetection section 2510. Whether the driver is drowsing may be decided.The in-vehicle information detection unit 2500 may subject a collectedaudio signal to a noise canceling process or other process.

The integrated control unit 2600 controls the actions within the motorvehicle control system 2000 as a whole in accordance with variousprograms. An input section 2800 is connected to the integrated controlunit 2600. The input section 2800 is realized, for example, by a touchpanel, buttons, a microphone, switches, levers, or others on which inputoperation can be made. The input section 2800 may be, for example, aremote control apparatus based on infrared radiation or other radiowaves or an external connection apparatus such as mobile phone, PDA(Personal Digital Assistant), or others capable of manipulating themotor vehicle control system 2000. The input section 2800 may be, forexample, a camera, and in this case, a passenger can input informationby gesture. Further, the input section 2800 may include an input controlcircuit that generates an input signal based on the above informationinput by a passenger or others by using the input section 2800 andoutputs the input signal to the integrated control unit 2600. Passengersand so on input various data to the motor vehicle control system 2000and instruct the motor vehicle control system 2000 to process data.

The storage section 2690 may include a RAM (Random Access Memory) thatstores various programs executed by a microcomputer and a ROM (Read OnlyMemory) that stores various parameters, operation results, sensorvalues, and other data. Also, the storage section 2690 may be realizedby a magnetic storage device such as HDD (Hard Disc Drive),semiconductor storage device, optical storage device, magneto-opticalstorage device, or other device.

The general-purpose communication I/F 2620 is a general-purposecommunication interface that intermediates communication with variousapparatuses existing in an outside environment 2750. A cellularcommunication protocol such as GSM (registered trademark) (Global Systemof Mobile communications), WiMAX, LTE (Long Term Evolution), or LTE-A(LTE-Advanced) or other wireless communication protocol such as wirelessLAN (also referred to as Wi-Fi (registered trademark)) may beimplemented in the general-purpose communication I/F 2620. Thegeneral-purpose communication I/F 2620 may connect, for example, to anapparatus (e.g., application server or control server) existing on anexternal network (e.g., Internet, cloud network, or carrier's ownnetwork) via a base station and an access point. Also, thegeneral-purpose communication I/F 2620 may connect to a terminalexisting near the motor vehicle (e.g., pedestrian's or shop's terminalor MTC (Machine Type Communication) terminal) by using, for example, P2P(Peer To Peer) technology.

The dedicated communication I/F 2630 is a communication protocol thatsupports a communication protocol developed to be used in motorvehicles. A standard protocol such as WAVE (Wireless Access in VehicleEnvironment), a combination of IEEE802.11p, a lower layer, and IEEE1609,an upper layer, or DSRC (Dedicated Short Range Communications), forexample, may be implemented in the dedicated communication I/F 2630. Thededicated communication I/F 2630 typically carries out V2Xcommunication, a concept that includes one or more of vehicle to vehiclecommunication, vehicle to infrastructure communication, and vehicle topedestrian communication.

The positioning section 2640 carries out positioning by receiving a GNSSsignal (e.g., GPS signal from GPS (Global Positioning System) satellite)from a GNSS (Global Navigation Satellite System) satellite and generatesposition information including longitude, latitude, and altitude of themotor vehicle. It should be noted that the positioning section 2640 mayidentify the current position by exchanging signals with wireless accesspoints or acquire position information from a terminal such as mobilephone, PHS, or smartphone.

The beacon reception section 2650 acquires current position, trafficjams, road closures, required time, or other information by receivingradio waves or electromagnetic waves emitted from wireless stations orother apparatuses installed on roads. It should be noted that thefunctions of the beacon reception section 2650 may be included in thededicated communication I/F 2630.

The in-vehicle apparatus I/F 2660 is a communication interface thatintermediates communication between the microcomputer 2610 and variouspieces of equipment existing in the vehicle. The in-vehicle apparatusI/F 2660 may establish wireless connection by using a wirelesscommunication protocol such as wireless LAN, Bluetooth (registeredtrademark), NFC (Near Field Communication), or WUSB (Wireless USB).Also, the in-vehicle apparatus I/F 2660 may establish wired connectionby using a connection terminal which is not depicted (and a cable ifrequired). The in-vehicle apparatus I/F 2660 exchanges control signalsor data signals, for example, with a mobile apparatus or a wearableapparatus of a passenger, or an information apparatus carried into orinstalled in the motor vehicle.

The on-vehicle network I/F 2680 is an interface that intermediatescommunication between the microcomputer 2610 and the communicationnetwork 2010. The on-vehicle network I/F 2680 sends and receives signalsand others according to a given protocol supported by the communicationnetwork 2010.

The microcomputer 2610 of the integrated control unit 2600 controls themotor vehicle control system 2000 in accordance with various programsbased on information acquired via at least one of the general-purposecommunication I/F 2620, the dedicated communication I/F 2630, thepositioning section 2640, the beacon reception section 2650, thein-vehicle apparatus I/F 2660, and the on-vehicle network I/F 2680. Forexample, the microcomputer 2610 may calculate a control target value ofthe driving force generating apparatus, the steering mechanism, or thebrake apparatus on the basis of in-vehicle and out-vehicle informationacquired, and may output instruction of control with respect to thedrive-related control unit 2100. For example, the microcomputer 2610 mayperform cooperative control for motor vehicle collision avoidance, orimpact alleviation, follow-up traveling based on vehicle-to-vehicledistance, constant vehicle speed traveling, autonomous driving, and soon.

The microcomputer 2610 may create local map information includinginformation around the current position of the motor vehicle on thebasis of information acquired via at least one of the general-purposecommunication I/F 2620, the dedicated communication I/F 2630, thepositioning section 2640, the beacon reception section 2650, thein-vehicle apparatus I/F 2660, and the on-vehicle network I/F 2680.Also, the microcomputer 2610 may predict risks such as collision of themotor vehicle, approaching pedestrian, and entry into a closed road andgenerate a warning signal. A warning signal may be a signal that causesa warning tone to be produced or a warning lamp to be lit.

The audio/video output section 2670 sends at least either an audio orvideo output signal to an output apparatus that is capable of visuallyor auditorily notifying information to the motor vehicle's passenger oroutside of the vehicle. In the example depicted in FIG. 26, an audiospeaker 2710, a display section 2720, and an instrument panel 2730 aredepicted as output apparatuses. The display section 2720 may include,for example, at least one of an on-board display and a head-up display.The display section 2720 may include an AR (Augmented Reality) displayfunction. The output apparatus may be an apparatus other than the abovesuch as headphone, projector, or lamp. When the output apparatus is adisplay apparatus, the display apparatus visually displays resultsobtained by various processes performed by the microcomputer 2610 orinformation received from other control units in various forms such astext, image, table, and graph. Also, when the output apparatus is anaudio output apparatus, the audio output apparatus converts an audiosignal made up of audio data, acoustic data, or other data into ananalog signal and auditorily outputs the analog signal.

It should be noted that, in the example depicted in FIG. 26, at leasttwo control units connected via the communication network 2010 may becombined into a single control unit. Alternatively, each control unitmay include a plurality of control units. Further, the motor vehiclecontrol system 2000 may include a separate control unit that is notdepicted. Also, in the description given above, some or all of thefunctions assumed by any of the control units may be assumed by othercontrol unit. That is, as long as information is sent and received viathe communication network 2010, given arithmetic processing may beperformed by one of the control units. Similarly, a sensor or apparatusconnected to one of the control units may be connected to other controlunit so that the plurality of control units mutually send and receivedetection information via the communication network 2010.

In the motor vehicle control system 2000 described above, the drivingcontrol apparatus 11 according to the present embodiment described usingFIG. 1 is applicable to the integrated control unit 2600 of theapplication example depicted in FIG. 26. For example, the autonomousdriving control block 21, the personalization block 22, and the manualdriving control section 32 of the driving control apparatus 11 depictedin FIG. 1 correspond to the microcomputer 2610, the storage section2690, and the on-vehicle network I/F 2680 of the integrated control unit2600. For example, the integrated control unit 2600 can realizeautonomous driving safely by functioning as the autonomous drivingcontrol block 21. Also, the personalization block 22 can realizeautonomous driving tailored to preferences of each user by learning apersonalization function.

Also, at least some of the components of the driving control apparatus11 described using FIG. 1 may be realized in a module (e.g., integratedcircuit module configured on a single die) for the integrated controlunit 2600 depicted in FIG. 26. Alternatively, the driving controlapparatus 11 described using FIG. 1 may be realized by the plurality ofcontrol units of the motor vehicle control system 2000 depicted in FIG.26. That is, the detection section 34 may be realized by at least one ofthe out-vehicle information detection unit 2400 and the in-vehicleinformation detection unit 2500 of the motor vehicle control system 2000depicted in FIG. 26.

It should be noted that computer programs for realizing the respectivefunctions of the driving control apparatus 11 described using FIG. 1 canbe implemented in one of the control units. Also, a computer-readablerecording medium storing such computer programs can be provided. Therecording medium is, for example, a magnetic disk, an optical disc, amagneto-optical disc, a flash memory, and so on. Also, the abovecomputer programs may be delivered, for example, via a network ratherthan using a recording medium.

5. Second Application Example <Example of Performing the Processes bySoftware>

Incidentally, the series of processes described above can be performednot only by hardware but also by software. When the series of processesare performed by software, the program making up the software isinstalled to a computer built into dedicated hardware, a general-purposepersonal computer capable of performing various functions as variousprograms are installed thereto, and so on from a recording medium.

FIG. 28 illustrates a configuration example of a general-purposepersonal computer. This personal computer has a CPU (Central ProcessingUnit) 3001 built thereinto. An I/O interface 3005 is connected to theCPU 3001 via a bus 3004. A ROM (Read Only Memory) 3002 and a RAM (RandomAccess Memory) 3003 are connected to the I/O interface 3005.

An input section 3006, an output section 3007, a storage section 3008,and a communication section 3009 are connected to the I/O interface3005. The input section 3006 includes a keyboard, a mouse, and otherinput devices from which the user inputs operation commands. The outputsection 3007 outputs processing operation screens and processing resultimages. The storage section 3008 includes a hard disk drive and so onthat stores programs and various data. The communication section 3009includes a LAN (Local Area Network) adapter and so on that handlescommunication processes via a network, typically the Internet. A drive3010 is also connected to the I/O interface 3005. The drive 3010 readsdata from and writes data to a removable medium 3011 such as magneticdisk (including flexible disk), optical disc (including CD-ROM (CompactDisc-Read Only Memory), DVD (Digital Versatile Disc), magneto-opticaldisk (MD (Mini Disc)), or semiconductor memory.

The CPU 3001 performs various processes in accordance with the programstored in the ROM 3002 or the program read from the removable medium3011 such as magnetic disk, optical disc, magneto-optical disk, orsemiconductor memory, installed in the storage section 3008, and loadedinto the RAM 3003 from the storage section 3008. Data required for theCPU 3001 to perform various processes is also stored in the RAM 3003 asappropriate.

In the computer configured as described above, the series of processesdescribed above are performed as the CPU 3001 loads, for example, theprogram stored in the storage section 3008 into the RAM 3003 via the I/Ointerface 3005 and the bus 3004 for execution.

The program executed by the computer (CPU 3001) can be provided, forexample, recorded on the removable medium 3011 as a package medium.Alternatively, the program can be provided via a wired or wirelesstransmission medium such as local area network, the Internet, or digitalsatellite broadcasting.

In the computer, the program can be installed to the storage section3008 via the I/O interface 3005 as the removable recording medium 3011is inserted into the drive 3010. Also, the program can be received bythe communication section 3009 via a wired or wireless transmissionmedium such as a local area network, the Internet, or digital satellitebroadcasting and installed to the storage section 3008. In addition tothe above, the program can be installed, in advance, to the ROM 3002 orthe storage section 3008.

It should be noted that the program executed by the computer may be aprogram that performs the processes chronologically according to thesequence described in the present specification, or in parallel, or at anecessary time as when the program is called.

Also, in the present specification, a system refers to a set of aplurality of components (e.g., apparatuses, modules (parts)), and itdoes not matter whether or not all the components are accommodated inthe same housing. Therefore, a plurality of apparatuses accommodated indifferent housings and connected via a network and a single apparatushaving a plurality of modules accommodated in a single housing are bothsystems.

It should be noted that embodiments of the present disclosure are notlimited to that described above and can be modified in various wayswithout departing from the gist of the present disclosure.

For example, the present disclosure can have a cloud computingconfiguration in which a single function is shared among a plurality ofapparatuses and processed in a collaborative manner via a network.

Also, each of the steps described in the flowcharts may be not onlyperformed by a single apparatus but also shared and performed by aplurality of apparatuses.

Further, when a plurality of processes are included in a single step,the plurality of processes included in that single step can be not onlyperformed by a single apparatus but also shared and performed by aplurality of apparatuses.

It should be noted that the present disclosure can have the followingconfigurations:

<1> A driving control apparatus including:

a detection section adapted to detect a condition of a moving object;

a deliberate action determination section adapted to determine an actionof the moving object as a deliberate action on the basis of a detectionresult of the detection section;

a reflex action determination section adapted to determine, on the basisof the detection result of the detection section, an action of themoving object in a shorter time period than a process carried out by thedeliberate action determination section; and

an action control section adapted to control the action of the movingobject on the basis of the deliberate action and a reflex actiondetermined by the reflex action determination section.

<2> The driving control apparatus of feature <1>, in which

the deliberate action determination section includes:

-   -   a local processing section adapted to extract local information        around the moving object on the basis of the detection result of        the detection section;    -   a global processing section adapted to extract global        information in a wider area than around the moving object on the        basis of the detection result of the detection section; and    -   a behavior determination section adapted to determine an action        on the basis of the local information and the global        information.        <3> The driving control apparatus of feature <1>, in which

the action control section performs control such that if a conflictoccurs between the deliberate action and the reflex action, theoccurrence of the conflict is presented.

<4> The driving control apparatus of feature <3>, in which

the action control section resolves the conflict in response to inputfrom the driver and controls the action of the moving object on thebasis of the deliberate action and the reflex action.

<5> The driving control apparatus of feature <1>, in which

the action control section stores a plurality of resolution modes inadvance to deal with a conflict between the deliberate action and thereflex action, resolves the conflict in accordance with one of theplurality of resolution modes, and controls the action of the movingobject on the basis of the deliberate action and the reflex action.

<6> The driving control apparatus of feature <5>, in which

the resolution modes include:

-   -   a first resolution mode that gives priority to the deliberate        action or the reflex action;    -   a second resolution mode that selects ‘first come priority’ or        ‘replace with last come’ between the deliberate action and the        reflex action;    -   a third resolution mode that gives priority to the deliberate        action or the reflex action, whichever is higher in terms of        command priority level or action environment certainty level;    -   a fourth resolution mode that takes a weighted average or        majority decision using both the deliberate action and the        reflex action;    -   a fifth resolution mode that adds the fact that the deliberate        action and the reflex action are opposed to each other to the        input so that recalculation is performed by the two;    -   a sixth resolution mode that gives priority to the priority        level of the command itself for the deliberate action and the        reflex action;    -   a seventh resolution mode that stops the vehicle without issuing        either of the deliberate action or the reflex action or        maintains the current state; and    -   an eighth resolution mode that allows the driver of the moving        object to intervene.        <7> The driving control apparatus of feature <6>, in which

the action control section displays a slide bar that can be operated tospecify a parameter that is used when the deliberate action and thereflex action are determined and controls the action of the movingobject on the basis of the deliberate action and the reflex actiondetermined by using the parameter whose value is proportional to theposition of the slide bar operated by the driver.

<8> The driving control apparatus of feature <1>, in which

the action control section controls the action during autonomous drivingcontrol of the moving object on the basis of the deliberate action andthe reflex action.

<9> A driving control method including the steps of:

detecting a condition of a moving object;

determining an action of the moving object as a deliberate action on thebasis of a detection result of the condition of the moving object;

determining, on the basis of the detection result, an action of themoving object in a shorter time period than a process carried out by thedeliberate action determination section; and

controlling the action of the moving object on the basis of thedeliberate action and a reflex action determined in a shorter timeperiod than the process for determining the deliberate action.

<10> A program causing a computer to function as:

a detection section adapted to detect a condition of a moving object;

a deliberate action determination section adapted to determine an actionof the moving object as a deliberate action on the basis of a detectionresult of the detection section;

a reflex action determination section adapted to determine, on the basisof the detection result of the detection section, an action of themoving object in a shorter time period than a process carried out by thedeliberate action determination section; and

an action control section adapted to control the action of the movingobject on the basis of the deliberate action and a reflex actiondetermined by the reflex action determination section.

REFERENCE SIGNS LIST

-   11 Driving control apparatus-   12 Outside world-   13 Verification apparatus-   21 Autonomous driving control block-   22 Personalization block-   31 Operation section-   32 Manual driving control section-   33 Vehicle body action section-   34 Detection section-   51 Reflex action determination section-   52 Deliberate action determination section-   53 Autonomous driving control section-   54 Personalization function storage section-   71 Environment recognition section-   72 Local map processing section-   73 Global map processing section-   74 Route planning section-   75 Behavior planning section-   91 Personalization function learning section-   92 Learning result storage section-   93 Learning result verification section-   94 Verification result decision section-   95 Personalization function updating section-   181 Origin/destination random setup section-   182 Route generation section-   183 Checkpoint position calculation section-   184 Behavior determination model calculation section-   185 Simulator-   186 Event generation section-   187 State calculation section-   188 Sensor model/noise model generation section-   189 Recording section-   190 Verification section-   201 Verification section-   211 Personalization function learning section-   212 Learning result verification section-   221 Verification section-   231 Personalization function learning section-   232 Learning result verification section-   233 Verification result decision section-   234 Personalization function updating section

1. A driving control apparatus comprising: a detection section adaptedto detect a condition of a moving object; a deliberate actiondetermination section adapted to determine an action of the movingobject as a deliberate action on the basis of a detection result of thedetection section; a reflex action determination section adapted todetermine, on the basis of the detection result of the detectionsection, an action of the moving object in a shorter time period than aprocess carried out by the deliberate action determination section; andan action control section adapted to control the action of the movingobject on the basis of the deliberate action and a reflex actiondetermined by the reflex action determination section.
 2. The drivingcontrol apparatus of claim 1, wherein the deliberate actiondetermination section includes: a local processing section adapted toextract local information around the moving object on the basis of thedetection result of the detection section; a global processing sectionadapted to extract global information in a wider area than around themoving object on the basis of the detection result of the detectionsection; and a behavior determination section adapted to determine anaction on the basis of the local information and the global information.3. The driving control apparatus of claim 1, wherein the action controlsection performs control such that if a conflict occurs between thedeliberate action and the reflex action, the occurrence of the conflictis presented.
 4. The driving control apparatus of claim 3, wherein theaction control section resolves the conflict in response to input fromthe driver and controls the action of the moving object on the basis ofthe deliberate action and the reflex action.
 5. The driving controlapparatus of claim 1, wherein the action control section stores aplurality of resolution modes in advance to deal with a conflict betweenthe deliberate action and the reflex action, resolves the conflict inaccordance with one of the plurality of resolution modes, and controlsthe action of the moving object on the basis of the deliberate actionand the reflex action.
 6. The driving control apparatus of claim 5,wherein the resolution modes includes: a first resolution mode thatgives priority to the deliberate action or the reflex action; a secondresolution mode that selects ‘first come priority’ or ‘replace with lastcome’ between the deliberate action and the reflex action; a thirdresolution mode that gives priority to the deliberate action or thereflex action, whichever is higher in terms of command priority level oraction environment certainty level; a fourth resolution mode that takesa weighted average or majority decision using both the deliberate actionand the reflex action; a fifth resolution mode that adds the fact thatthe deliberate action and the reflex action are opposed to each other tothe input so that recalculation is performed by the two; a sixthresolution mode that gives priority to the priority level of the commanditself for the deliberate action and the reflex action; a seventhresolution mode that stops the vehicle without issuing either of thedeliberate action or the reflex action or maintains the current state;and an eighth resolution mode that allows the driver of the movingobject to intervene.
 7. The driving control apparatus of claim 6,wherein the action control section displays a slide bar that can beoperated to specify a parameter that is used when the deliberate actionand the reflex action are determined and controls the action of themoving object on the basis of the deliberate action and the reflexaction determined by using the parameter whose value is proportional tothe position of the slide bar operated by the driver.
 8. The drivingcontrol apparatus of claim 1, wherein the action control sectioncontrols the action during autonomous driving control of the movingobject on the basis of the deliberate action and the reflex action.
 9. Adriving control method comprising the steps of: detecting a condition ofa moving object; determining an action of the moving object as adeliberate action on the basis of a detection result of the condition ofthe moving object; determining, on the basis of the detection result, anaction of the moving object in a shorter time period than a processcarried out by the deliberate action determination section; andcontrolling the action of the moving object on the basis of thedeliberate action and a reflex action determined in a shorter timeperiod than the process for determining the deliberate action.
 10. Aprogram causing a computer to function as: a detection section adaptedto detect a condition of a moving object; a deliberate actiondetermination section adapted to determine an action of the movingobject as a deliberate action on the basis of a detection result of thedetection section; a reflex action determination section adapted todetermine, on the basis of the detection result of the detectionsection, an action of the moving object in a shorter time period than aprocess carried out by the deliberate action determination section; andan action control section adapted to control the action of the movingobject on the basis of the deliberate action and a reflex actiondetermined by the reflex action determination section.